system

Abstract

We provide the system. [Solution] A means of receiving electronic content as input, analyzing the text data within the content, and estimating the emotional state of a character, A means for selecting an appropriate voice from pre-prepared voice actor models based on an estimated emotional state and generating speech, A means for automatically generating sound effects corresponding to the scene's depiction and combining them with the generated audio, A means for outputting the generated audio content, A system that includes this.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] [The demand for providing content such as comics and e-books with voice has been increasing, but there are problems that traditional voice content production is costly and time-consuming. Also, adding acoustic effects corresponding to multiple languages and various scenes is complicated, and there is a problem that it is difficult to easily voice all works.]

Means for Solving the Problems

[0005] [This invention provides a system that takes electronic content as input, estimates a character's emotions, and automatically generates voice and scene-appropriate sound effects based on those emotions. Specifically, it uses emotion analysis means to select an appropriate voice actor model for each character to generate voice, and then automatically adds scene-specific sound effects. This makes it possible to generate high-quality voice-over content quickly and at low cost. It also includes means to support voice-over conversion of multilingual content.]

[0006] "Electronic content" refers to [information and data provided in digital format, including media formats such as text, images, audio, and video].

[0007] A "character" is [a person, animal, or fictional being that appears in a story or illustration, and is depicted as having a specific personality or emotions].

[0008] "Emotional state" refers to the emotional situation or mental state expressed by a character, and can be of various types, such as joy, sadness, anger, and surprise.

[0009] A "voice actor model" is a speech synthesis algorithm used to imitate a specific voice quality or speaking style, and is used to generate the voice of a virtual character.

[0010] "Generating speech" is the process of synthesizing human-sounding speech based on input text or other data.

[0011] "Sound effects" refer to the sound effects played in conjunction with movies, animations, audio content, etc., and are used to emphasize ambient sounds or specific actions appropriate to the scene.

[0012] "Multilingual support" refers to the ability to handle multiple different languages, meaning that content can be used appropriately in different language environments.

[0013] "A specific scene designated by the user" refers to a particular scene or situation in the story that the user has specifically selected or instructed to select through their device. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is a system that takes electronic content as input and converts it into audio content. It begins with the user selecting electronic content via a terminal and uploading it to a server. The server analyzes the text data from the received content and detects the character's emotional state. Based on this detected emotional information, the optimal voice actor model is selected, and appropriate audio is generated.

[0036] Furthermore, the server takes scene descriptions into account and automatically generates necessary sound effects. For example, in a rain scene, it adds rain sounds. These sound effects and audio tracks are combined on the server side to generate integrated audio content. In this generation process, it is also possible to generate audio in a language specified by the user to support multiple languages.

[0037] As a concrete example, suppose a user inputs an e-comic titled "The Adventurer's Story." The server analyzes the story's text and detects scenes where the characters' emotions are heightened. In these scenes, it generates voices that mimic energetic voices, and if it's a battle scene, it adds sound effects of swords and shields. Through this process, the user can experience the story as more immersive audio content. This embodiment of the invention is designed to enable fast, low-cost, and high-quality output.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The user uses their device to select an electronic content file and begin uploading it to the server.

[0041] Step 2:

[0042] The terminal sends the selected electronic content to the server, which then checks the format of the received file. If the file format is inappropriate, an error message is sent to the user.

[0043] Step 3:

[0044] The server analyzes the electronic content in the appropriate format and prepares to separate text data and image data page by page.

[0045] Step 4:

[0046] The server uses natural language processing technology to extract character dialogue from text data and performs emotion analysis. As a result, the character's emotional state is estimated.

[0047] Step 5:

[0048] The server selects an appropriate voice actor model based on the emotion analysis results and generates audio data for the lines. The generated audio data is then matched to each line of dialogue spoken by the character.

[0049] Step 6:

[0050] The server analyzes the image data scene and selects appropriate sound effects from a predefined sound effects library. In some cases, sound effects may be automatically generated based on the scene's depiction.

[0051] Step 7:

[0052] The server integrates the generated audio data and sound effect tracks, and adjusts the overall audio track.

[0053] Step 8:

[0054] The server generates a download link for the completed audio content and notifies the user's device.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] When playing electronic content with sound, conventional systems often require manual effort to generate emotionally appropriate voices and add sound effects appropriate to the scene, which is time-consuming. Furthermore, there are limitations in multilingual support and the addition of individual sound effects, resulting in insufficient usability and a poor overall user experience.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes means for receiving information data as input and analyzing the text data within the information to estimate the emotional state of a character; means for selecting an appropriate voice from a pre-prepared voice model based on the estimated emotional state and generating the voice; and means for automatically generating sound effects corresponding to the scene description and combining them with the generated voice. This makes it possible to automatically and efficiently generate information with voice that corresponds to the emotions and scenes of the content input by the user.

[0060] "Information data" is a general term for digital information such as text, images, and audio data that is stored, processed, communicated, or displayed in electronic format.

[0061] "Text data" refers to information represented as a string of characters, and is digital data that includes sentences, words, and symbols.

[0062] "Character's emotional state" refers to the result of estimating the psychological or emotional state exhibited by a character within text data through analysis.

[0063] A "speech model" is the underlying data or algorithm for speech synthesis technology, designed to mimic specific speech characteristics or voice qualities.

[0064] "Scene description" refers to any description that visually or audibly represents a scene or environment presented within information data.

[0065] "Sound effects" are acoustic elements added to audio information for the purpose of enhancing realism or atmosphere.

[0066] A "user-specified instruction" is a string of characters or a command used to execute an operation or instruction entered by the user into the system.

[0067] "Information with audio" refers to information that includes audio data, making it accessible not only visually but also aurally.

[0068] This invention provides a system for playing electronic information with sound. This system consists of components such as a user, a terminal, and a server, and each component works in coordination to enable efficient content generation.

[0069] The user first uses their device to select the source data for the audio content and uploads this data to the server. This process uses a standard file selection interface and handles various digital content formats, including text files, ebooks, and digital comics. The user's selected data is securely stored in the server's database and then moves on to the next processing stage.

[0070] Upon receiving uploaded data, the server first uses natural language processing (NLP) techniques to analyze the text data. This analysis process utilizes a generative AI model to estimate the emotional state of each character. The server employs state-of-the-art machine learning algorithms and datasets to achieve more accurate emotion detection.

[0071] After the emotional state is detected, the server selects the appropriate voice model from several options and synthesizes the speech. High-resolution speech synthesis software is used for this process, enabling natural and emotionally responsive speech expression.

[0072] Furthermore, the server generates sound effects based on the scene description in the information data and combines the audio track and the sound effect track. It utilizes a sound effects library to automatically generate and add rain sounds, for example, according to a prompt such as "rain scene."

[0073] The system supports multilingual information data, and the server generates audio appropriate for each language based on the information specified by the user. The final generated audio information is provided to the user's device in a format that can be redownloaded. Users can play the content and enjoy the information both visually and aurally.

[0074] As a concrete example, a user inputs an e-comic titled "The Adventurer's Story," and the server uses the prompt "Analyze the emotions in this text, generate audio using an appropriate voice model, and add sound effects appropriate to the scene" to analyze the context of the story. This example allows the user to experience the story in a more immersive way.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The user selects the information data they wish to convert to audio via their device and uploads it to the server. This process utilizes a standard file selection screen to send the information data to the specified upload location on the server. The input is the information data, and the output is the saving of the data to the server.

[0078] Step 2:

[0079] The server receives the information data and analyzes the text data using natural language processing (NLP) techniques. Based on this analysis, it estimates the emotional state of the characters within the text. The input is the uploaded text data, and the output is the analyzed emotional state data. A generative AI model is used for the analysis.

[0080] Step 3:

[0081] The server selects the optimal voice from multiple voice models based on the estimated emotional state and performs speech synthesis. The input is emotional state data and a voice model, and the output is voice data that matches the emotion. Realistic voice expression is achieved through a generative AI model.

[0082] Step 4:

[0083] The server automatically generates sound effects based on the scene description in the information data and combines them with the previously generated audio data. The input is the scene information and the audio synthesis result from the information data, and the output is the integrated information data with audio. Specifically, prompt statements are used, including instructions such as "Add rain sounds in rain scenes."

[0084] Step 5:

[0085] The server generates the final audio-enhanced information data and exports it in the format specified by the user. At this stage, the user receives the content in a format that can be redownloaded. The input is the integrated audio data generated in step 4, and the output is the audio-enhanced file available to the user.

[0086] (Application Example 1)

[0087] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0088] In modern digital content consumption, there is a need for easy ways for users to obtain immersive audio experiences. However, existing technologies make it difficult to quickly and cost-effectively generate voices that respond to emotions and scenes, and to adjust sound effects based on individual user requests. As a result, there is a challenge in realizing sophisticated audio content experiences through personal smart devices.

[0089] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0090] In this invention, the server includes means for receiving electronic content as input and analyzing the text data within the content to estimate the emotional state of a character; means for selecting an appropriate voice from a pre-prepared voice synthesis model based on the estimated emotional state and generating the voice; and means for automatically generating sound effects corresponding to the depiction of the scene and integrating them with the generated voice. This makes it possible for users to quickly and inexpensively enjoy a high-quality, immersive digital content experience with sound using communication devices.

[0091] "Electronic content" refers to digital information media that users can acquire, store, and view via computers and communication devices.

[0092] "Character data" refers to information composed of characters and symbols that is processed, analyzed, and displayed electronically.

[0093] "Character emotional state" refers to information that indicates the psychological situation and emotions expressed by characters within a story or content.

[0094] A "speech synthesis model" is a computer program or algorithm used to convert text data into speech data.

[0095] "Scene description" refers to descriptions or visual representations used to explain a specific place, time, or situation in a story or content.

[0096] "Sound effects" are audio elements added to audiovisual media to emphasize a particular atmosphere or event.

[0097] "Communication equipment" refers to electronic devices used to send and receive information such as voice, data, and video between subscribers.

[0098] "Digital content with audio" refers to digital information media that are distributed or stored with added audio information.

[0099] The system for implementing this invention mainly consists of a server and a user's terminal. The user uploads electronic content from the terminal to the server using a communication device. The server extracts text data from the received electronic content and estimates the character's emotional state using a natural language processing library. Specifically, libraries such as SpaCy and NLTK are used for this purpose. Based on the emotional state, an appropriate voice is generated using a speech synthesis library (e.g., Google® Text-to-Speech API).

[0100] Furthermore, the server generates sound effects appropriate to each scene. These sound effects are intended to artificially complement the depiction of a particular scene and refer to a pre-created sound effects library. These sound effects are dynamically customized by a generating AI model and used to enhance the atmosphere of the scene.

[0101] Finally, the server integrates the audio and sound effects to generate digital content with sound. This process allows users to have a more immersive audio experience. For example, if a story called "The Hero's Adventure" is uploaded to the server, the adventure scenes can be reproduced with sounds such as sword swings and footsteps, along with voiceovers that emphasize positive emotions.

[0102] An example of an input prompt for a generative AI model is: "Based on the analyzed text data, please voice the story in a voice that matches the character's emotions. Please add sound effects to the following scene: {scene details}"

[0103] Thus, the present invention can provide users with a rich audio content experience quickly and at low cost by integrating voice generation and sound effects.

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] The user selects electronic content using a terminal and uploads it to the server. The input in this step is the electronic content, and the output is the server receiving the content. The user operates a communication device to send the target content file through the server's designated upload interface.

[0107] Step 2:

[0108] The server extracts text data from the received electronic content. The input for this step is the uploaded electronic content, and the output is the extracted text data for analysis. The server filters the text information within the content, extracting and organizing character dialogue and explanations.

[0109] Step 3:

[0110] The server analyzes text data to estimate the character's emotional state. The input for this step is the extracted text data, and the output is the estimated emotional state. The server uses a natural language processing library (e.g., SpaCy) to evaluate the emotion from the context and classify it into categories such as "anger" or "joy."

[0111] Step 4:

[0112] The server selects a speech synthesis model based on the estimated emotional state and generates speech. The input for this step is the emotional state and text data, and the output is the generated speech data. The server selects a speech synthesis model appropriate for the emotion and uses the generative AI model to convert the input text into speech.

[0113] Step 5:

[0114] The server generates sound effects corresponding to the scene's depiction and integrates them with the generated audio. The input for this step is scene details and audio data, and the output is integrated digital content with audio. The server selects appropriate sounds from a sound effects library and synthesizes them with the audio data, timing them correctly.

[0115] Step 6:

[0116] The server outputs the generated digital content with audio to the user's terminal. The input for this step is integrated digital content with audio, and the output is an audio file or streaming data that the user can listen to. The user can then enjoy an immersive audio experience through their terminal.

[0117] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0118] This invention provides a system that personalizes the conversion of electronic content into audio content while taking user emotions into consideration. The process begins with the user selecting electronic content via a terminal and uploading it to a server. The server analyzes the text data of the received content and estimates the emotional state of the characters. Based on this estimation, it selects a voice actor model and generates the voice. Furthermore, it generates sound effects corresponding to the scene's depiction, and by combining these, the completed audio content is produced.

[0119] A key feature of this invention is that the server can also consider the user's emotional state. The terminal collects user emotional data in real time and transmits it to the server. The emotion engine analyzes the user's emotions, and for example, if the user is relaxed, it adjusts the voice tone gently to improve the user experience. It is also possible to dynamically adjust content generation in response to changes in the user's emotions.

[0120] For example, suppose a user inputs electronic content of a story called "Magical Adventure." The server analyzes the story's text and estimates the emotions expressed in the main characters' lines. During this process, the terminal collects emotional data from the user's facial expressions, which is then analyzed by an emotion engine. If the server determines that the user is excited, it adjusts the audio content by adding a more forceful intonation. In this way, the user can experience more personalized audio content. Embodiments of the present invention make it possible to provide a rich entertainment experience that is personalized according to the user's emotional state.

[0121] The following describes the processing flow.

[0122] Step 1:

[0123] The user uses their device to select the electronic content files they want to convert and then starts uploading them to the server.

[0124] Step 2:

[0125] The device transmits electronic content to the server. Simultaneously, the device collects emotional data in real time, such as the user's facial expressions and tone of voice, and transmits this data to the server.

[0126] Step 3:

[0127] The server checks the format of the received electronic content and determines whether it is in a valid format. If the format is inappropriate, it notifies the user of an error message via the terminal.

[0128] Step 4:

[0129] The server analyzes the text data of the electronic content and uses natural language processing to extract the characters' lines and emotional states.

[0130] Step 5:

[0131] The emotion engine analyzes user emotion data received in real time and estimates the user's current emotional state. The results are then provided to the server.

[0132] Step 6:

[0133] The server combines the character's emotional state with the estimated user's emotional state to select the optimal voice actor model and generate audio data. It adjusts the tone and speed of the voice as needed.

[0134] Step 7:

[0135] The server selects sound effects based on the scene content, combines the generated audio data with the sound effects, and creates an audio track. During this process, the overall balance is adjusted, taking into account the user's emotions.

[0136] Step 8:

[0137] The server outputs the generated audio content and provides a download link to the device. The user can then view the resulting content on their device.

[0138] (Example 2)

[0139] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0140] In the modern age, electronic data functions as a diverse source of information, but a problem is that text-based information alone cannot fully evoke emotional immersion in users. Furthermore, existing audio content generation systems struggle to provide personalized experiences that reflect each user's emotional state.

[0141] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0142] In this invention, the server includes means for receiving electronic data as input and analyzing the text information within the data to estimate the emotional state of a character; means for acquiring the user's emotional state using a sensor device and reflecting it in voice generation; and means for automatically generating sound corresponding to the situation of the scene and integrating it with the generated voice. This makes it possible to generate personalized voice content that matches the user's emotions.

[0143] "Electronic data" refers to information such as text, images, and audio that is represented in a digital format.

[0144] "Text information" refers to information composed of characters and phrases within electronic data.

[0145] "Character emotional state" refers to the psychological state and emotional expression of the characters or beings that appear in the story or content.

[0146] A "speech synthesis model" is a system or algorithm used to artificially generate human speech based on input data.

[0147] "Acoustics" refers to sounds or sound effects that can be perceived by hearing, and are generated to suit the context.

[0148] A "sensor device" refers to a device that detects physical or chemical properties and outputs them as electrical signals.

[0149] "Speech generation" is the process of creating speech that is understandable to the listener using electronic data and models.

[0150] A "scene" refers to a specific place or setting in which a story or situation unfolds.

[0151] This invention is a system that converts electronic data into audio data using a user's terminal, a server, and a generative AI model. The user first uses their terminal to select the electronic data they want to convert to audio and uploads it to the server. The server analyzes the received text information using natural language processing software. Open-source natural language processing libraries can be used for this analysis. The server then uses an emotion analysis model to estimate the emotional state of a character based on the analysis results.

[0152] Next, the server selects a speech synthesis model and uses it to generate sounds appropriate to the character's emotional state and the situation. This involves using a deep learning model to generate human speech from text. During speech generation, the AI ​​model also automatically generates sound effects appropriate to the situation, and these sound effects are integrated with the speech.

[0153] Furthermore, to enhance the user's individual experience, the device uses sensor devices to measure the user's emotional state in real time and transmits this data to a server. The server analyzes the user's emotional data to reflect the individual's emotional state in the generated audio data.

[0154] As a concrete example, consider a scenario where a user inputs a fantasy adventure story as electronic data. The server analyzes the story's text, estimates the characters' emotions, and then generates appropriate voices. If the emotional data indicates that the user is excited, the server adjusts the voice by adding a stronger intonation.

[0155] Examples of prompts include, "Voice the characters in this fantasy adventure story in a calm voice tone appropriate for when the user is relaxed," and "Generate audio content with a strong intonation to match the user's level of excitement."

[0156] In this way, the system can generate personalized voice data that responds to the user's emotions, providing a rich experience.

[0157] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0158] Step 1:

[0159] The user selects the electronic data they want to convert to audio using a terminal. Electronic data (e.g., text-based stories or documents) is required as input. The terminal prepares the selected data and gets ready to upload it to the server. Throughout this process, the user can operate intuitively via a graphical user interface (GUI).

[0160] Step 2:

[0161] The server receives electronic data uploaded from the terminal. The input is the electronic data itself. The server uses natural language processing software to analyze the text information within the data and extract character dialogue and scene interpretations. This analysis process efficiently identifies the constituent elements within the data and builds a foundation for estimating emotional states.

[0162] Step 3:

[0163] The server estimates the emotional state of the characters based on the analyzed text information. The input is the text analysis results from the previous step. Using an emotion analysis model, the emotions embedded in each line of dialogue are quantified, and a voice actor model is selected based on this information. The output is estimated emotion data corresponding to each character.

[0164] Step 4:

[0165] The server generates voice using the selected voice actor model. The input is the emotion data estimated in step 3. The speech synthesis model generates voice data that matches the character's emotions and tone. The generated voice is adjusted to be realistic and expressive.

[0166] Step 5:

[0167] The server generates sound corresponding to the scenes in the story. The input is information about the scenes in the story. A generative AI model creates sound effects appropriate for each scene and integrates them with the audio data. The output of this step is comprehensive audio data that combines the audio and sound effects.

[0168] Step 6:

[0169] The device collects the user's emotional state using sensor devices. Inputs include the user's facial expressions and biometric information. The device analyzes this data and transmits it to the server in real time. Outputs are numerical data representing the user's emotional state.

[0170] Step 7:

[0171] The server analyzes the user's emotional data and incorporates it into the generated audio data. The input is the user emotional data obtained in step 6. The tone and tempo of the audio are adjusted to match the user's state. This makes it possible to provide the user with a personalized experience.

[0172] Step 8:

[0173] The server sends the adjusted audio data to the device. The final output is personalized audio electronic data tailored to the user's emotions. The user can play it on their device and enjoy emotionally rich content.

[0174] (Application Example 2)

[0175] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0176] In recent years, there has been a growing demand for personalized audio content that adapts to users' emotions. However, conventional audio generation systems have been insufficient in adjusting audio to take into account the user's emotional state, making it difficult to provide a personalized experience. Furthermore, there is a lack of systems that support multiple languages ​​and have the flexibility to add sound effects individually to specific scenes. As a result, there is a challenge in that the personalized experience for users is limited.

[0177] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0178] In this invention, the server includes means for receiving electronic information as input and analyzing the text data within the information to estimate the emotional state of a character; means for recognizing the emotional state of the user and adjusting the voice tone based on that recognition; and means for enabling the addition of sound effects individually for specific situations specified by the user. This makes it possible to personalize audio content according to the user's emotions and provide a richer entertainment experience.

[0179] "Electronic information" refers to all data stored or transmitted in digital format, and specifically includes formats such as text, audio, images, and video.

[0180] "Text data" refers to a collection of string information that makes up a document, and is the subject of analysis using natural language processing and other methods.

[0181] "Character emotional state" refers to the emotions expressed by the characters appearing in the text, and specifically includes psychological states such as joy, anger, sadness, and happiness.

[0182] A "voice model" is an algorithm or software for digital speech synthesis that imitates specific voice characteristics or timbre.

[0183] "Sound effects" are audio elements added to visual or audio content to emphasize specific scenes or emotions.

[0184] "User emotional state" refers to the real-time emotional tendencies and psychological state exhibited by the system user, and is inferred from facial expressions, tone of voice, and behavior.

[0185] "Voice tone" refers to the acoustic characteristics of a voice, such as its pitch, strength, and intonation, and is a means of conveying emotions and atmosphere.

[0186] "Personalization" is a concept that refers to the provision of customized experiences and services based on the specific needs and preferences of individual users.

[0187] This invention relates to a system that provides users with personalized audio content based on their emotions. The system mainly consists of a user's terminal, a cloud server, an audio generation engine, an emotion analysis engine, and an audio effect generation module.

[0188] The user's device is responsible for inputting electronic information and sending the analysis results of that information to the cloud server. The device includes a camera and microphone, which are used to collect the user's facial expressions and voice tone in real time and send the user's emotional state to the cloud server.

[0189] The server utilizes computing resources in the cloud to analyze input text data and estimate the character's emotional state. This analysis employs natural language processing techniques and AI-based emotion estimation algorithms. Specifically, Microsoft® Azure® Emotion API or equivalent software is used for emotion analysis.

[0190] Based on the estimated emotional state, the speech generation engine selects an appropriate speech model and generates the speech. APIs such as the Google Text-to-Speech API are useful for speech generation, allowing for a variety of voice tones and intonations.

[0191] Furthermore, to automatically generate sound effects appropriate to the situation, sound effect libraries such as FMOD are used. This enhances the acoustic elements to match the scene setting, resulting in a deeper sense of immersion.

[0192] As a concrete example, consider a scenario where a user wants to listen to an audio version of the adventure novel "The Wizard's Journey" while on a crowded train. Based on the user's input on their device, the server adjusts the audio tone to one that promotes relaxation. This allows the user to comfortably enjoy the story without feeling tired, even in the confined space of a train.

[0193] Examples of prompt statements include the following:

[0194] "Upload the text for 'The Wizard's Journey,' and if the user's emotions are fatigued, generate audio content by adding a calming voice and soothing music."

[0195] This makes it possible for the present invention to achieve a high level of personalization that adapts to the user's emotional state and to provide a rich entertainment experience.

[0196] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0197] Step 1:

[0198] The user's device inputs electronic information. The user selects desired content, and the device's camera and microphone collect facial expressions and voice tone. This collected data is sent to the server as input data used for subsequent sentiment analysis.

[0199] Step 2:

[0200] The server analyzes the electronic information received from the user. It uses natural language processing techniques to analyze text data and estimate the emotional state of the character. In this process, for example, a generative AI model is used to detect the emotional flags in the text, and the emotional information related to the text is output as an analysis result.

[0201] Step 3:

[0202] The server analyzes the user's emotional state. It inputs the received real-time facial expression data and voice tone into an emotion analysis engine to estimate the user's current emotional state. The primary tool used here is an emotion analysis library (e.g., Microsoft Azure Emotion API), which outputs emotional characteristics (e.g., relaxed, excited, tired, etc.).

[0203] Step 4:

[0204] The server generates speech based on the character's and the user's emotional state. It selects a voice model with a voice tone corresponding to the estimated emotion and generates the speech using the Google Text-to-Speech API. The generated speech data is the output of the step.

[0205] Step 5:

[0206] The server selects and generates sound effects. It requests sound effects appropriate to the situation from libraries such as the FMOD library, generating sound data that complements the atmosphere of the scene. This results in output sound effect files that provide a rich audio experience.

[0207] Step 6:

[0208] The server combines the generated audio and sound effects to create the final audio content. Using audio editing tools, the audio data and sound effects are adjusted and combined along the timeline, and output as the final content file.

[0209] Step 7:

[0210] The server sends the completed audio content to the user's device. It adjusts the content for smooth streaming playback and then provides it to the user. The user experiences the personalized audio content through their smartphone.

[0211] In this way, the system realizes a system that provides personalized audio content that reflects the user's emotional state through each step.

[0212] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0213] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0214] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0215] [Second Embodiment]

[0216] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0217] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0218] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0219] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0220] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0221] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0222] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0223] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0224] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0225] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0226] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0227] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0228] This invention is a system that takes electronic content as input and converts it into audio content. It begins with the user selecting electronic content via a terminal and uploading it to a server. The server analyzes the text data from the received content and detects the character's emotional state. Based on this detected emotional information, the optimal voice actor model is selected, and appropriate audio is generated.

[0229] Furthermore, the server takes scene descriptions into account and automatically generates necessary sound effects. For example, in a rain scene, it adds rain sounds. These sound effects and audio tracks are combined on the server side to generate integrated audio content. In this generation process, it is also possible to generate audio in a language specified by the user to support multiple languages.

[0230] As a concrete example, suppose a user inputs an e-comic titled "The Adventurer's Story." The server analyzes the story's text and detects scenes where the characters' emotions are heightened. In these scenes, it generates voices that mimic energetic voices, and if it's a battle scene, it adds sound effects of swords and shields. Through this process, the user can experience the story as more immersive audio content. This embodiment of the invention is designed to enable fast, low-cost, and high-quality output.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] The user uses their device to select an electronic content file and begin uploading it to the server.

[0234] Step 2:

[0235] The terminal sends the selected electronic content to the server, which then checks the format of the received file. If the file format is inappropriate, an error message is sent to the user.

[0236] Step 3:

[0237] The server analyzes the electronic content in the appropriate format and prepares to separate text data and image data page by page.

[0238] Step 4:

[0239] The server uses natural language processing technology to extract character dialogue from text data and performs emotion analysis. As a result, the character's emotional state is estimated.

[0240] Step 5:

[0241] The server selects an appropriate voice actor model based on the emotion analysis results and generates audio data for the lines. The generated audio data is then matched to each line of dialogue spoken by the character.

[0242] Step 6:

[0243] The server analyzes the image data scene and selects appropriate sound effects from a predefined sound effects library. In some cases, sound effects may be automatically generated based on the scene's depiction.

[0244] Step 7:

[0245] The server integrates the generated audio data and sound effect tracks, and adjusts the overall audio track.

[0246] Step 8:

[0247] The server generates a download link for the completed audio content and notifies the user's device.

[0248] (Example 1)

[0249] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0250] When playing electronic content with sound, conventional systems often require manual effort to generate emotionally appropriate voices and add sound effects appropriate to the scene, which is time-consuming. Furthermore, there are limitations in multilingual support and the addition of individual sound effects, resulting in insufficient usability and a poor overall user experience.

[0251] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0252] In this invention, the server includes means for receiving information data as input and analyzing the text data within the information to estimate the emotional state of a character; means for selecting an appropriate voice from a pre-prepared voice model based on the estimated emotional state and generating the voice; and means for automatically generating sound effects corresponding to the scene description and combining them with the generated voice. This makes it possible to automatically and efficiently generate information with voice that corresponds to the emotions and scenes of the content input by the user.

[0253] "Information data" is a general term for digital information such as text, images, and audio data that is stored, processed, communicated, or displayed in electronic format.

[0254] "Text data" refers to information represented as a string of characters, and is digital data that includes sentences, words, and symbols.

[0255] "Character's emotional state" refers to the result of estimating the psychological or emotional state exhibited by a character within text data through analysis.

[0256] A "speech model" is the underlying data or algorithm for speech synthesis technology, designed to mimic specific speech characteristics or voice qualities.

[0257] "Scene description" refers to any description that visually or audibly represents a scene or environment presented within information data.

[0258] "Sound effects" are acoustic elements added to audio information for the purpose of enhancing realism or atmosphere.

[0259] A "user-specified instruction" is a string of characters or a command used to execute an operation or instruction entered by the user into the system.

[0260] "Information with audio" refers to information that includes audio data, making it accessible not only visually but also aurally.

[0261] This invention provides a system for playing electronic information with sound. This system consists of components such as a user, a terminal, and a server, and each component works in coordination to enable efficient content generation.

[0262] The user first uses their device to select the source data for the audio content and uploads this data to the server. This process uses a standard file selection interface and handles various digital content formats, including text files, ebooks, and digital comics. The user's selected data is securely stored in the server's database and then moves on to the next processing stage.

[0263] Upon receiving uploaded data, the server first uses natural language processing (NLP) techniques to analyze the text data. This analysis process utilizes a generative AI model to estimate the emotional state of each character. The server employs state-of-the-art machine learning algorithms and datasets to achieve more accurate emotion detection.

[0264] After the emotional state is detected, the server selects the appropriate voice model from several options and synthesizes the speech. High-resolution speech synthesis software is used for this process, enabling natural and emotionally responsive speech expression.

[0265] Furthermore, the server generates sound effects based on the scene description in the information data and combines the audio track and the sound effect track. It utilizes a sound effects library to automatically generate and add rain sounds, for example, according to a prompt such as "rain scene."

[0266] The system supports multilingual information data, and the server generates audio appropriate for each language based on the information specified by the user. The final generated audio information is provided to the user's device in a format that can be redownloaded. Users can play the content and enjoy the information both visually and aurally.

[0267] As a concrete example, a user inputs an e-comic titled "The Adventurer's Story," and the server uses the prompt "Analyze the emotions in this text, generate audio using an appropriate voice model, and add sound effects appropriate to the scene" to analyze the context of the story. This example allows the user to experience the story in a more immersive way.

[0268] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0269] Step 1:

[0270] The user selects the information data they wish to convert to audio via their device and uploads it to the server. This process utilizes a standard file selection screen to send the information data to the specified upload location on the server. The input is the information data, and the output is the saving of the data to the server.

[0271] Step 2:

[0272] The server receives the information data and analyzes the text data using natural language processing (NLP) techniques. Based on this analysis, it estimates the emotional state of the characters within the text. The input is the uploaded text data, and the output is the analyzed emotional state data. A generative AI model is used for the analysis.

[0273] Step 3:

[0274] The server selects the optimal voice from multiple voice models based on the estimated emotional state and performs speech synthesis. The input is emotional state data and a voice model, and the output is voice data that matches the emotion. Realistic voice expression is achieved through a generative AI model.

[0275] Step 4:

[0276] The server automatically generates sound effects based on the scene description in the information data and combines them with the previously generated audio data. The input is the scene information and the audio synthesis result from the information data, and the output is the integrated information data with audio. Specifically, prompt statements are used, including instructions such as "Add rain sounds in rain scenes."

[0277] Step 5:

[0278] The server generates the final audio-enhanced information data and exports it in the format specified by the user. At this stage, the user receives the content in a format that can be redownloaded. The input is the integrated audio data generated in step 4, and the output is the audio-enhanced file available to the user.

[0279] (Application Example 1)

[0280] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0281] In modern digital content consumption, there is a need for easy ways for users to obtain immersive audio experiences. However, existing technologies make it difficult to quickly and cost-effectively generate voices that respond to emotions and scenes, and to adjust sound effects based on individual user requests. As a result, there is a challenge in realizing sophisticated audio content experiences through personal smart devices.

[0282] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0283] In this invention, the server includes: means for receiving electronic content as input, analyzing the character data in the content, and estimating the emotional state of the character; means for selecting appropriate audio from a pre-prepared voice synthesis model based on the estimated emotional state and generating the audio; and means for automatically generating acoustic effects corresponding to the description of the scene and integrating them with the generated audio. As a result, [it becomes possible for users to enjoy a high-quality and immersive audio digital content experience quickly and at low cost using a communication device].

[0284] "Electronic content" is a digital information medium that can be acquired, stored, and viewed by users via computers or communication devices.

[0285] "Character data" refers to information composed of characters and symbols, and indicates content that is electronically processed, analyzed, and displayed.

[0286] "The emotional state of the character" refers to information indicating the psychological situation and emotions expressed by the characters in a story or content.

[0287] "Voice synthesis model" is a computer program or algorithm used to convert text data into voice data.

[0288] "Description of the scene" is a description or visual representation for explaining a specific location, time, and situation in a story or content.

[0289] "Acoustic effect" is an audio element added to audiovisual media to emphasize a specific atmosphere or event.

[0290] "Communication device" is an electronic device for transmitting and receiving information such as voice, data, and video between subscribers.

[0291] "Digital content with audio" is a digital information medium distributed or stored with audio information added.

[0292] The system for implementing this invention mainly consists of a server and a user's terminal. The user uploads electronic content from the terminal to the server using a communication device. The server extracts text data from the received electronic content and estimates the character's emotional state using a natural language processing library. Specifically, libraries such as SpaCy and NLTK are used for this purpose. Based on the emotional state, an appropriate voice is generated using a speech synthesis library (e.g., Google Text-to-Speech API).

[0293] Furthermore, the server generates sound effects appropriate to each scene. These sound effects are intended to artificially complement the depiction of a particular scene and refer to a pre-created sound effects library. These sound effects are dynamically customized by a generating AI model and used to enhance the atmosphere of the scene.

[0294] Finally, the server integrates the audio and sound effects to generate digital content with sound. This process allows users to have a more immersive audio experience. For example, if a story called "The Hero's Adventure" is uploaded to the server, the adventure scenes can be reproduced with sounds such as sword swings and footsteps, along with voiceovers that emphasize positive emotions.

[0295] An example of an input prompt for a generative AI model is: "Based on the analyzed text data, please voice the story in a voice that matches the character's emotions. Please add sound effects to the following scene: {scene details}"

[0296] Thus, the present invention can provide users with a rich audio content experience quickly and at low cost by integrating voice generation and sound effects.

[0297] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0298] Step 1:

[0299] The user selects electronic content using a terminal and uploads it to the server. The input in this step is the electronic content, and the output is the server receiving the content. The user operates a communication device to send the target content file through the server's designated upload interface.

[0300] Step 2:

[0301] The server extracts text data from the received electronic content. The input for this step is the uploaded electronic content, and the output is the extracted text data for analysis. The server filters the text information within the content, extracting and organizing character dialogue and explanations.

[0302] Step 3:

[0303] The server analyzes text data to estimate the character's emotional state. The input for this step is the extracted text data, and the output is the estimated emotional state. The server uses a natural language processing library (e.g., SpaCy) to evaluate the emotion from the context and classify it into categories such as "anger" or "joy."

[0304] Step 4:

[0305] The server selects a speech synthesis model based on the estimated emotional state and generates speech. The input for this step is the emotional state and text data, and the output is the generated speech data. The server selects a speech synthesis model appropriate for the emotion and uses the generative AI model to convert the input text into speech.

[0306] Step 5:

[0307] The server generates acoustic effects according to the description of the scene and integrates them with the generated voice. The input of this step is the details of the scene and voice data, and the output is digital content with integrated voice. The server selects appropriate sounds from the sound effect library and synthesizes them in accordance with the timing of the voice data.

[0308] Step 6:

[0309] The server outputs the generated digital content with voice to the user terminal. The input of this step is the digital content with integrated voice, and the output is an audible voice file or streaming data for the user. The user can enjoy an immersive audio experience through the terminal.

[0310] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0311] The present invention is a system that realizes personalization considering the user's emotion when converting electronic content into content with voice. It starts with the user selecting electronic content through the terminal and uploading it to the server. The server analyzes the text data of the received content and estimates the emotional state of the character. Based on this estimation result, a voice actor model is selected to generate voice. Furthermore, sound effects corresponding to the description of the scene are generated, and the completed content with voice is generated by combining them.

[0312] As a feature of the present invention, the server can also consider the user's emotional state. The terminal collects the user's emotion data in real time and transmits it to the server. The emotion engine analyzes the user's emotion. For example, if the user is in a relaxed state, the voice tone is gently adjusted to improve the user experience. Also, it is possible to dynamically adjust the generation of content according to the change in the user's emotion.

[0313] For example, suppose a user inputs electronic content of a story called "Magical Adventure." The server analyzes the story's text and estimates the emotions expressed in the main characters' lines. During this process, the terminal collects emotional data from the user's facial expressions, which is then analyzed by an emotion engine. If the server determines that the user is excited, it adjusts the audio content by adding a more forceful intonation. In this way, the user can experience more personalized audio content. Embodiments of the present invention make it possible to provide a rich entertainment experience that is personalized according to the user's emotional state.

[0314] The following describes the processing flow.

[0315] Step 1:

[0316] The user uses their device to select the electronic content files they want to convert and then starts uploading them to the server.

[0317] Step 2:

[0318] The device transmits electronic content to the server. Simultaneously, the device collects emotional data in real time, such as the user's facial expressions and tone of voice, and transmits this data to the server.

[0319] Step 3:

[0320] The server checks the format of the received electronic content and determines whether it is in a valid format. If the format is inappropriate, it notifies the user of an error message via the terminal.

[0321] Step 4:

[0322] The server analyzes the text data of the electronic content and uses natural language processing to extract the characters' lines and emotional states.

[0323] Step 5:

[0324] The emotion engine analyzes user emotion data received in real time and estimates the user's current emotional state. The results are then provided to the server.

[0325] Step 6:

[0326] The server combines the character's emotional state with the estimated user's emotional state to select the optimal voice actor model and generate audio data. It adjusts the tone and speed of the voice as needed.

[0327] Step 7:

[0328] The server selects sound effects based on the scene content, combines the generated audio data with the sound effects, and creates an audio track. During this process, the overall balance is adjusted, taking into account the user's emotions.

[0329] Step 8:

[0330] The server outputs the generated audio content and provides a download link to the device. The user can then view the resulting content on their device.

[0331] (Example 2)

[0332] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0333] In the modern age, electronic data functions as a diverse source of information, but a problem is that text-based information alone cannot fully evoke emotional immersion in users. Furthermore, existing audio content generation systems struggle to provide personalized experiences that reflect each user's emotional state.

[0334] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0335] In this invention, the server includes means for receiving electronic data as input and analyzing the text information within the data to estimate the emotional state of a character; means for acquiring the user's emotional state using a sensor device and reflecting it in voice generation; and means for automatically generating sound corresponding to the situation of the scene and integrating it with the generated voice. This makes it possible to generate personalized voice content that matches the user's emotions.

[0336] "Electronic data" refers to information such as text, images, and audio that is represented in a digital format.

[0337] "Text information" refers to information composed of characters and phrases within electronic data.

[0338] "Character emotional state" refers to the psychological state and emotional expression of the characters or beings that appear in the story or content.

[0339] A "speech synthesis model" is a system or algorithm used to artificially generate human speech based on input data.

[0340] "Acoustics" refers to sounds or sound effects that can be perceived by hearing, and are generated to suit the context.

[0341] A "sensor device" refers to a device that detects physical or chemical properties and outputs them as electrical signals.

[0342] "Speech generation" is the process of creating speech that is understandable to the listener using electronic data and models.

[0343] A "scene" refers to a specific place or setting in which a story or situation unfolds.

[0344] This invention is a system that converts electronic data into audio data using a user's terminal, a server, and a generative AI model. The user first uses their terminal to select the electronic data they want to convert to audio and uploads it to the server. The server analyzes the received text information using natural language processing software. Open-source natural language processing libraries can be used for this analysis. The server then uses an emotion analysis model to estimate the emotional state of a character based on the analysis results.

[0345] Next, the server selects a speech synthesis model and uses it to generate sounds appropriate to the character's emotional state and the situation. This involves using a deep learning model to generate human speech from text. During speech generation, the AI ​​model also automatically generates sound effects appropriate to the situation, and these sound effects are integrated with the speech.

[0346] Furthermore, to enhance the user's individual experience, the device uses sensor devices to measure the user's emotional state in real time and transmits this data to a server. The server analyzes the user's emotional data to reflect the individual's emotional state in the generated audio data.

[0347] As a concrete example, consider a scenario where a user inputs a fantasy adventure story as electronic data. The server analyzes the story's text, estimates the characters' emotions, and then generates appropriate voices. If the emotional data indicates that the user is excited, the server adjusts the voice by adding a stronger intonation.

[0348] Examples of prompts include, "Voice the characters in this fantasy adventure story in a calm voice tone appropriate for when the user is relaxed," and "Generate audio content with a strong intonation to match the user's level of excitement."

[0349] In this way, the system can generate personalized voice data that responds to the user's emotions, providing a rich experience.

[0350] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0351] Step 1:

[0352] The user selects the electronic data they want to convert to audio using a terminal. Electronic data (e.g., text-based stories or documents) is required as input. The terminal prepares the selected data and gets ready to upload it to the server. Throughout this process, the user can operate intuitively via a graphical user interface (GUI).

[0353] Step 2:

[0354] The server receives electronic data uploaded from the terminal. The input is the electronic data itself. The server uses natural language processing software to analyze the text information within the data and extract character dialogue and scene interpretations. This analysis process efficiently identifies the constituent elements within the data and builds a foundation for estimating emotional states.

[0355] Step 3:

[0356] The server estimates the emotional state of the characters based on the analyzed text information. The input is the text analysis results from the previous step. Using an emotion analysis model, the emotions embedded in each line of dialogue are quantified, and a voice actor model is selected based on this information. The output is estimated emotion data corresponding to each character.

[0357] Step 4:

[0358] The server generates voice using the selected voice actor model. The input is the emotion data estimated in step 3. The speech synthesis model generates voice data that matches the character's emotions and tone. The generated voice is adjusted to be realistic and expressive.

[0359] Step 5:

[0360] The server generates sound corresponding to the scenes in the story. The input is information about the scenes in the story. A generative AI model creates sound effects appropriate for each scene and integrates them with the audio data. The output of this step is comprehensive audio data that combines the audio and sound effects.

[0361] Step 6:

[0362] The device collects the user's emotional state using sensor devices. Inputs include the user's facial expressions and biometric information. The device analyzes this data and transmits it to the server in real time. Outputs are numerical data representing the user's emotional state.

[0363] Step 7:

[0364] The server analyzes the user's emotional data and incorporates it into the generated audio data. The input is the user emotional data obtained in step 6. The tone and tempo of the audio are adjusted to match the user's state. This makes it possible to provide the user with a personalized experience.

[0365] Step 8:

[0366] The server sends the adjusted audio data to the device. The final output is personalized audio electronic data tailored to the user's emotions. The user can play it on their device and enjoy emotionally rich content.

[0367] (Application Example 2)

[0368] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0369] In recent years, there has been a growing demand for personalized audio content that adapts to users' emotions. However, conventional audio generation systems have been insufficient in adjusting audio to take into account the user's emotional state, making it difficult to provide a personalized experience. Furthermore, there is a lack of systems that support multiple languages ​​and have the flexibility to add sound effects individually to specific scenes. As a result, there is a challenge in that the personalized experience for users is limited.

[0370] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0371] In this invention, the server includes means for receiving electronic information as input and analyzing the text data within the information to estimate the emotional state of a character; means for recognizing the emotional state of the user and adjusting the voice tone based on that recognition; and means for enabling the addition of sound effects individually for specific situations specified by the user. This makes it possible to personalize audio content according to the user's emotions and provide a richer entertainment experience.

[0372] "Electronic information" refers to all data stored or transmitted in digital format, and specifically includes formats such as text, audio, images, and video.

[0373] "Text data" refers to a collection of string information that makes up a document, and is the subject of analysis using natural language processing and other methods.

[0374] "Character emotional state" refers to the emotions expressed by the characters appearing in the text, and specifically includes psychological states such as joy, anger, sadness, and happiness.

[0375] A "voice model" is an algorithm or software for digital speech synthesis that imitates specific voice characteristics or timbre.

[0376] "Sound effects" are audio elements added to visual or audio content to emphasize specific scenes or emotions.

[0377] "User emotional state" refers to the real-time emotional tendencies and psychological state exhibited by the system user, and is inferred from facial expressions, tone of voice, and behavior.

[0378] "Voice tone" refers to the acoustic characteristics of a voice, such as its pitch, strength, and intonation, and is a means of conveying emotions and atmosphere.

[0379] "Personalization" is a concept that refers to the provision of customized experiences and services based on the specific needs and preferences of individual users.

[0380] This invention relates to a system that provides users with personalized audio content based on their emotions. The system mainly consists of a user's terminal, a cloud server, an audio generation engine, an emotion analysis engine, and an audio effect generation module.

[0381] The user's device is responsible for inputting electronic information and sending the analysis results of that information to the cloud server. The device includes a camera and microphone, which are used to collect the user's facial expressions and voice tone in real time and send the user's emotional state to the cloud server.

[0382] The server utilizes computing resources in the cloud to analyze input text data and estimate the character's emotional state. This analysis employs natural language processing techniques and AI-based emotion estimation algorithms. Specifically, the Microsoft Azure Emotion API or equivalent software is used for emotion analysis.

[0383] Based on the estimated emotional state, the speech generation engine selects an appropriate speech model and generates the speech. APIs such as the Google Text-to-Speech API are useful for speech generation, allowing for a variety of voice tones and intonations.

[0384] Furthermore, to automatically generate sound effects appropriate to the situation, sound effect libraries such as FMOD are used. This enhances the acoustic elements to match the scene setting, resulting in a deeper sense of immersion.

[0385] As a concrete example, consider a scenario where a user wants to listen to an audio version of the adventure novel "The Wizard's Journey" while on a crowded train. Based on the user's input on their device, the server adjusts the audio tone to one that promotes relaxation. This allows the user to comfortably enjoy the story without feeling tired, even in the confined space of a train.

[0386] Examples of prompt statements include the following:

[0387] "Upload the text for 'The Wizard's Journey,' and if the user's emotions are fatigued, generate audio content by adding a calming voice and soothing music."

[0388] This makes it possible for the present invention to achieve a high level of personalization that adapts to the user's emotional state and to provide a rich entertainment experience.

[0389] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0390] Step 1:

[0391] The user's device inputs electronic information. The user selects desired content, and the device's camera and microphone collect facial expressions and voice tone. This collected data is sent to the server as input data used for subsequent sentiment analysis.

[0392] Step 2:

[0393] The server analyzes the electronic information received from the user. It uses natural language processing techniques to analyze text data and estimate the emotional state of the character. In this process, for example, a generative AI model is used to detect the emotional flags in the text, and the emotional information related to the text is output as an analysis result.

[0394] Step 3:

[0395] The server analyzes the user's emotional state. It inputs the received real-time facial expression data and voice tone into an emotion analysis engine to estimate the user's current emotional state. The primary tool used here is an emotion analysis library (e.g., Microsoft Azure Emotion API), which outputs emotional characteristics (e.g., relaxed, excited, tired, etc.).

[0396] Step 4:

[0397] The server generates speech based on the character's and the user's emotional state. It selects a voice model with a voice tone corresponding to the estimated emotion and generates the speech using the Google Text-to-Speech API. The generated speech data is the output of the step.

[0398] Step 5:

[0399] The server selects and generates sound effects. It requests sound effects appropriate to the situation from libraries such as the FMOD library, generating sound data that complements the atmosphere of the scene. This results in output sound effect files that provide a rich audio experience.

[0400] Step 6:

[0401] The server combines the generated audio and sound effects to create the final audio content. Using audio editing tools, the audio data and sound effects are adjusted and combined along the timeline, and output as the final content file.

[0402] Step 7:

[0403] The server sends the completed audio content to the user's device. It adjusts the content for smooth streaming playback and then provides it to the user. The user experiences the personalized audio content through their smartphone.

[0404] In this way, the system realizes a system that provides personalized audio content that reflects the user's emotional state through each step.

[0405] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0406] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0407] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0408] [Third Embodiment]

[0409] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0410] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0411] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0412] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0413] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0414] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0415] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0416] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0417] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0418] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0419] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0420] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0421] This invention is a system that takes electronic content as input and converts it into audio content. It begins with the user selecting electronic content via a terminal and uploading it to a server. The server analyzes the text data from the received content and detects the character's emotional state. Based on this detected emotional information, the optimal voice actor model is selected, and appropriate audio is generated.

[0422] Furthermore, the server takes scene descriptions into account and automatically generates necessary sound effects. For example, in a rain scene, it adds rain sounds. These sound effects and audio tracks are combined on the server side to generate integrated audio content. In this generation process, it is also possible to generate audio in a language specified by the user to support multiple languages.

[0423] As a concrete example, suppose a user inputs an e-comic titled "The Adventurer's Story." The server analyzes the story's text and detects scenes where the characters' emotions are heightened. In these scenes, it generates voices that mimic energetic voices, and if it's a battle scene, it adds sound effects of swords and shields. Through this process, the user can experience the story as more immersive audio content. This embodiment of the invention is designed to enable fast, low-cost, and high-quality output.

[0424] The following describes the processing flow.

[0425] Step 1:

[0426] The user uses their device to select an electronic content file and begin uploading it to the server.

[0427] Step 2:

[0428] The terminal sends the selected electronic content to the server, which then checks the format of the received file. If the file format is inappropriate, an error message is sent to the user.

[0429] Step 3:

[0430] The server analyzes the electronic content in the appropriate format and prepares to separate text data and image data page by page.

[0431] Step 4:

[0432] The server uses natural language processing technology to extract character dialogue from text data and performs emotion analysis. As a result, the character's emotional state is estimated.

[0433] Step 5:

[0434] The server selects an appropriate voice actor model based on the emotion analysis results and generates audio data for the lines. The generated audio data is then matched to each line of dialogue spoken by the character.

[0435] Step 6:

[0436] The server analyzes the image data scene and selects appropriate sound effects from a predefined sound effects library. In some cases, sound effects may be automatically generated based on the scene's depiction.

[0437] Step 7:

[0438] The server integrates the generated audio data and sound effect tracks, and adjusts the overall audio track.

[0439] Step 8:

[0440] The server generates a download link for the completed audio content and notifies the user's device.

[0441] (Example 1)

[0442] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0443] When playing electronic content with sound, conventional systems often require manual effort to generate emotionally appropriate voices and add sound effects appropriate to the scene, which is time-consuming. Furthermore, there are limitations in multilingual support and the addition of individual sound effects, resulting in insufficient usability and a poor overall user experience.

[0444] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0445] In this invention, the server includes means for receiving information data as input and analyzing the text data within the information to estimate the emotional state of a character; means for selecting an appropriate voice from a pre-prepared voice model based on the estimated emotional state and generating the voice; and means for automatically generating sound effects corresponding to the scene description and combining them with the generated voice. This makes it possible to automatically and efficiently generate information with voice that corresponds to the emotions and scenes of the content input by the user.

[0446] "Information data" is a general term for digital information such as text, images, and audio data that is stored, processed, communicated, or displayed in electronic format.

[0447] "Text data" refers to information represented as a string of characters, and is digital data that includes sentences, words, and symbols.

[0448] "Character's emotional state" refers to the result of estimating the psychological or emotional state exhibited by a character within text data through analysis.

[0449] A "speech model" is the underlying data or algorithm for speech synthesis technology, designed to mimic specific speech characteristics or voice qualities.

[0450] "Scene description" refers to any description that visually or audibly represents a scene or environment presented within information data.

[0451] "Sound effects" are acoustic elements added to audio information for the purpose of enhancing realism or atmosphere.

[0452] A "user-specified instruction" is a string of characters or a command used to execute an operation or instruction entered by the user into the system.

[0453] "Information with audio" refers to information that includes audio data, making it accessible not only visually but also aurally.

[0454] This invention provides a system for playing electronic information with sound. This system consists of components such as a user, a terminal, and a server, and each component works in coordination to enable efficient content generation.

[0455] The user first uses their device to select the source data for the audio content and uploads this data to the server. This process uses a standard file selection interface and handles various digital content formats, including text files, ebooks, and digital comics. The user's selected data is securely stored in the server's database and then moves on to the next processing stage.

[0456] Upon receiving uploaded data, the server first uses natural language processing (NLP) techniques to analyze the text data. This analysis process utilizes a generative AI model to estimate the emotional state of each character. The server employs state-of-the-art machine learning algorithms and datasets to achieve more accurate emotion detection.

[0457] After the emotional state is detected, the server selects the appropriate voice model from several options and synthesizes the speech. High-resolution speech synthesis software is used for this process, enabling natural and emotionally responsive speech expression.

[0458] Furthermore, the server generates sound effects based on the scene description in the information data and combines the audio track and the sound effect track. It utilizes a sound effects library to automatically generate and add rain sounds, for example, according to a prompt such as "rain scene."

[0459] The system supports multilingual information data, and the server generates audio appropriate for each language based on the information specified by the user. The final generated audio information is provided to the user's device in a format that can be redownloaded. Users can play the content and enjoy the information both visually and aurally.

[0460] As a concrete example, a user inputs an e-comic titled "The Adventurer's Story," and the server uses the prompt "Analyze the emotions in this text, generate audio using an appropriate voice model, and add sound effects appropriate to the scene" to analyze the context of the story. This example allows the user to experience the story in a more immersive way.

[0461] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0462] Step 1:

[0463] The user selects the information data they wish to convert to audio via their device and uploads it to the server. This process utilizes a standard file selection screen to send the information data to the specified upload location on the server. The input is the information data, and the output is the saving of the data to the server.

[0464] Step 2:

[0465] The server receives the information data and analyzes the text data using natural language processing (NLP) techniques. Based on this analysis, it estimates the emotional state of the characters within the text. The input is the uploaded text data, and the output is the analyzed emotional state data. A generative AI model is used for the analysis.

[0466] Step 3:

[0467] The server selects the optimal voice from multiple voice models based on the estimated emotional state and performs speech synthesis. The input is emotional state data and a voice model, and the output is voice data that matches the emotion. Realistic voice expression is achieved through a generative AI model.

[0468] Step 4:

[0469] The server automatically generates sound effects based on the scene description in the information data and combines them with the previously generated audio data. The input is the scene information and the audio synthesis result from the information data, and the output is the integrated information data with audio. Specifically, prompt statements are used, including instructions such as "Add rain sounds in rain scenes."

[0470] Step 5:

[0471] The server generates the final audio-enhanced information data and exports it in the format specified by the user. At this stage, the user receives the content in a format that can be redownloaded. The input is the integrated audio data generated in step 4, and the output is the audio-enhanced file available to the user.

[0472] (Application Example 1)

[0473] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0474] In modern digital content consumption, there is a need for easy ways for users to obtain immersive audio experiences. However, existing technologies make it difficult to quickly and cost-effectively generate voices that respond to emotions and scenes, and to adjust sound effects based on individual user requests. As a result, there is a challenge in realizing sophisticated audio content experiences through personal smart devices.

[0475] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0476] In this invention, the server includes means for receiving electronic content as input and analyzing the text data within the content to estimate the emotional state of a character; means for selecting an appropriate voice from a pre-prepared voice synthesis model based on the estimated emotional state and generating the voice; and means for automatically generating sound effects corresponding to the depiction of the scene and integrating them with the generated voice. This makes it possible for users to quickly and inexpensively enjoy a high-quality, immersive digital content experience with sound using communication devices.

[0477] "Electronic content" refers to digital information media that users can acquire, store, and view via computers and communication devices.

[0478] "Character data" refers to information composed of characters and symbols that is processed, analyzed, and displayed electronically.

[0479] "Character emotional state" refers to information that indicates the psychological situation and emotions expressed by characters within a story or content.

[0480] A "speech synthesis model" is a computer program or algorithm used to convert text data into speech data.

[0481] "Scene description" refers to descriptions or visual representations used to explain a specific place, time, or situation in a story or content.

[0482] "Sound effects" are audio elements added to audiovisual media to emphasize a particular atmosphere or event.

[0483] "Communication equipment" refers to electronic devices used to send and receive information such as voice, data, and video between subscribers.

[0484] "Digital content with audio" refers to digital information media that are distributed or stored with added audio information.

[0485] The system for implementing this invention mainly consists of a server and a user's terminal. The user uploads electronic content from the terminal to the server using a communication device. The server extracts text data from the received electronic content and estimates the character's emotional state using a natural language processing library. Specifically, libraries such as SpaCy and NLTK are used for this purpose. Based on the emotional state, an appropriate voice is generated using a speech synthesis library (e.g., Google Text-to-Speech API).

[0486] Furthermore, the server generates sound effects appropriate to each scene. These sound effects are intended to artificially complement the depiction of a particular scene and refer to a pre-created sound effects library. These sound effects are dynamically customized by a generating AI model and used to enhance the atmosphere of the scene.

[0487] Finally, the server integrates the audio and sound effects to generate digital content with sound. This process allows users to have a more immersive audio experience. For example, if a story called "The Hero's Adventure" is uploaded to the server, the adventure scenes can be reproduced with sounds such as sword swings and footsteps, along with voiceovers that emphasize positive emotions.

[0488] An example of an input prompt for a generative AI model is: "Based on the analyzed text data, please voice the story in a voice that matches the character's emotions. Please add sound effects to the following scene: {scene details}"

[0489] Thus, the present invention can provide users with a rich audio content experience quickly and at low cost by integrating voice generation and sound effects.

[0490] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0491] Step 1:

[0492] The user selects electronic content using a terminal and uploads it to the server. The input in this step is the electronic content, and the output is the server receiving the content. The user operates a communication device to send the target content file through the server's designated upload interface.

[0493] Step 2:

[0494] The server extracts text data from the received electronic content. The input for this step is the uploaded electronic content, and the output is the extracted text data for analysis. The server filters the text information within the content, extracting and organizing character dialogue and explanations.

[0495] Step 3:

[0496] The server analyzes text data to estimate the character's emotional state. The input for this step is the extracted text data, and the output is the estimated emotional state. The server uses a natural language processing library (e.g., SpaCy) to evaluate the emotion from the context and classify it into categories such as "anger" or "joy."

[0497] Step 4:

[0498] The server selects a speech synthesis model based on the estimated emotional state and generates speech. The input for this step is the emotional state and text data, and the output is the generated speech data. The server selects a speech synthesis model appropriate for the emotion and uses the generative AI model to convert the input text into speech.

[0499] Step 5:

[0500] The server generates sound effects corresponding to the scene's depiction and integrates them with the generated audio. The input for this step is scene details and audio data, and the output is integrated digital content with audio. The server selects appropriate sounds from a sound effects library and synthesizes them with the audio data, timing them correctly.

[0501] Step 6:

[0502] The server outputs the generated digital content with audio to the user's terminal. The input for this step is integrated digital content with audio, and the output is an audio file or streaming data that the user can listen to. The user can then enjoy an immersive audio experience through their terminal.

[0503] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0504] This invention provides a system that personalizes the conversion of electronic content into audio content while taking user emotions into consideration. The process begins with the user selecting electronic content via a terminal and uploading it to a server. The server analyzes the text data of the received content and estimates the emotional state of the characters. Based on this estimation, it selects a voice actor model and generates the voice. Furthermore, it generates sound effects corresponding to the scene's depiction, and by combining these, the completed audio content is produced.

[0505] A key feature of this invention is that the server can also consider the user's emotional state. The terminal collects user emotional data in real time and transmits it to the server. The emotion engine analyzes the user's emotions, and for example, if the user is relaxed, it adjusts the voice tone gently to improve the user experience. It is also possible to dynamically adjust content generation in response to changes in the user's emotions.

[0506] For example, suppose a user inputs electronic content of a story called "Magical Adventure." The server analyzes the story's text and estimates the emotions expressed in the main characters' lines. During this process, the terminal collects emotional data from the user's facial expressions, which is then analyzed by an emotion engine. If the server determines that the user is excited, it adjusts the audio content by adding a more forceful intonation. In this way, the user can experience more personalized audio content. Embodiments of the present invention make it possible to provide a rich entertainment experience that is personalized according to the user's emotional state.

[0507] The following describes the processing flow.

[0508] Step 1:

[0509] The user uses their device to select the electronic content files they want to convert and then starts uploading them to the server.

[0510] Step 2:

[0511] The device transmits electronic content to the server. Simultaneously, the device collects emotional data in real time, such as the user's facial expressions and tone of voice, and transmits this data to the server.

[0512] Step 3:

[0513] The server checks the format of the received electronic content and determines whether it is in a valid format. If the format is inappropriate, it notifies the user of an error message via the terminal.

[0514] Step 4:

[0515] The server analyzes the text data of the electronic content and uses natural language processing to extract the characters' lines and emotional states.

[0516] Step 5:

[0517] The emotion engine analyzes user emotion data received in real time and estimates the user's current emotional state. The results are then provided to the server.

[0518] Step 6:

[0519] The server combines the character's emotional state with the estimated user's emotional state to select the optimal voice actor model and generate audio data. It adjusts the tone and speed of the voice as needed.

[0520] Step 7:

[0521] The server selects sound effects based on the scene content, combines the generated audio data with the sound effects, and creates an audio track. During this process, the overall balance is adjusted, taking into account the user's emotions.

[0522] Step 8:

[0523] The server outputs the generated audio content and provides a download link to the device. The user can then view the resulting content on their device.

[0524] (Example 2)

[0525] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0526] In the modern age, electronic data functions as a diverse source of information, but a problem is that text-based information alone cannot fully evoke emotional immersion in users. Furthermore, existing audio content generation systems struggle to provide personalized experiences that reflect each user's emotional state.

[0527] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0528] In this invention, the server includes means for receiving electronic data as input and analyzing the text information within the data to estimate the emotional state of a character; means for acquiring the user's emotional state using a sensor device and reflecting it in voice generation; and means for automatically generating sound corresponding to the situation of the scene and integrating it with the generated voice. This makes it possible to generate personalized voice content that matches the user's emotions.

[0529] "Electronic data" refers to information such as text, images, and audio that is represented in a digital format.

[0530] "Text information" refers to information composed of characters and phrases within electronic data.

[0531] "Character emotional state" refers to the psychological state and emotional expression of the characters or beings that appear in the story or content.

[0532] A "speech synthesis model" is a system or algorithm used to artificially generate human speech based on input data.

[0533] "Acoustics" refers to sounds or sound effects that can be perceived by hearing, and are generated to suit the context.

[0534] A "sensor device" refers to a device that detects physical or chemical properties and outputs them as electrical signals.

[0535] "Speech generation" is the process of creating speech that is understandable to the listener using electronic data and models.

[0536] A "scene" refers to a specific place or setting in which a story or situation unfolds.

[0537] This invention is a system that converts electronic data into audio data using a user's terminal, a server, and a generative AI model. The user first uses their terminal to select the electronic data they want to convert to audio and uploads it to the server. The server analyzes the received text information using natural language processing software. Open-source natural language processing libraries can be used for this analysis. The server then uses an emotion analysis model to estimate the emotional state of a character based on the analysis results.

[0538] Next, the server selects a speech synthesis model and uses it to generate sounds appropriate to the character's emotional state and the situation. This involves using a deep learning model to generate human speech from text. During speech generation, the AI ​​model also automatically generates sound effects appropriate to the situation, and these sound effects are integrated with the speech.

[0539] Furthermore, to enhance the user's individual experience, the device uses sensor devices to measure the user's emotional state in real time and transmits this data to a server. The server analyzes the user's emotional data to reflect the individual's emotional state in the generated audio data.

[0540] As a concrete example, consider a scenario where a user inputs a fantasy adventure story as electronic data. The server analyzes the story's text, estimates the characters' emotions, and then generates appropriate voices. If the emotional data indicates that the user is excited, the server adjusts the voice by adding a stronger intonation.

[0541] Examples of prompts include, "Voice the characters in this fantasy adventure story in a calm voice tone appropriate for when the user is relaxed," and "Generate audio content with a strong intonation to match the user's level of excitement."

[0542] In this way, the system can generate personalized voice data that responds to the user's emotions, providing a rich experience.

[0543] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0544] Step 1:

[0545] The user selects the electronic data they want to convert to audio using a terminal. Electronic data (e.g., text-based stories or documents) is required as input. The terminal prepares the selected data and gets ready to upload it to the server. Throughout this process, the user can operate intuitively via a graphical user interface (GUI).

[0546] Step 2:

[0547] The server receives electronic data uploaded from the terminal. The input is the electronic data itself. The server uses natural language processing software to analyze the text information within the data and extract character dialogue and scene interpretations. This analysis process efficiently identifies the constituent elements within the data and builds a foundation for estimating emotional states.

[0548] Step 3:

[0549] The server estimates the emotional state of the characters based on the analyzed text information. The input is the text analysis results from the previous step. Using an emotion analysis model, the emotions embedded in each line of dialogue are quantified, and a voice actor model is selected based on this information. The output is estimated emotion data corresponding to each character.

[0550] Step 4:

[0551] The server generates voice using the selected voice actor model. The input is the emotion data estimated in step 3. The speech synthesis model generates voice data that matches the character's emotions and tone. The generated voice is adjusted to be realistic and expressive.

[0552] Step 5:

[0553] The server generates sound corresponding to the scenes in the story. The input is information about the scenes in the story. A generative AI model creates sound effects appropriate for each scene and integrates them with the audio data. The output of this step is comprehensive audio data that combines the audio and sound effects.

[0554] Step 6:

[0555] The device collects the user's emotional state using sensor devices. Inputs include the user's facial expressions and biometric information. The device analyzes this data and transmits it to the server in real time. Outputs are numerical data representing the user's emotional state.

[0556] Step 7:

[0557] The server analyzes the user's emotional data and incorporates it into the generated audio data. The input is the user emotional data obtained in step 6. The tone and tempo of the audio are adjusted to match the user's state. This makes it possible to provide the user with a personalized experience.

[0558] Step 8:

[0559] The server sends the adjusted audio data to the device. The final output is personalized audio electronic data tailored to the user's emotions. The user can play it on their device and enjoy emotionally rich content.

[0560] (Application Example 2)

[0561] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0562] In recent years, there has been a growing demand for personalized audio content that adapts to users' emotions. However, conventional audio generation systems have been insufficient in adjusting audio to take into account the user's emotional state, making it difficult to provide a personalized experience. Furthermore, there is a lack of systems that support multiple languages ​​and have the flexibility to add sound effects individually to specific scenes. As a result, there is a challenge in that the personalized experience for users is limited.

[0563] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0564] In this invention, the server includes means for receiving electronic information as input and analyzing the text data within the information to estimate the emotional state of a character; means for recognizing the emotional state of the user and adjusting the voice tone based on that recognition; and means for enabling the addition of sound effects individually for specific situations specified by the user. This makes it possible to personalize audio content according to the user's emotions and provide a richer entertainment experience.

[0565] "Electronic information" refers to all data stored or transmitted in digital format, and specifically includes formats such as text, audio, images, and video.

[0566] "Text data" refers to a collection of string information that makes up a document, and is the subject of analysis using natural language processing and other methods.

[0567] "Character emotional state" refers to the emotions expressed by the characters appearing in the text, and specifically includes psychological states such as joy, anger, sadness, and happiness.

[0568] A "voice model" is an algorithm or software for digital speech synthesis that imitates specific voice characteristics or timbre.

[0569] "Sound effects" are audio elements added to visual or audio content to emphasize specific scenes or emotions.

[0570] "User emotional state" refers to the real-time emotional tendencies and psychological state exhibited by the system user, and is inferred from facial expressions, tone of voice, and behavior.

[0571] "Voice tone" refers to the acoustic characteristics of a voice, such as its pitch, strength, and intonation, and is a means of conveying emotions and atmosphere.

[0572] "Personalization" is a concept that refers to the provision of customized experiences and services based on the specific needs and preferences of individual users.

[0573] This invention relates to a system that provides users with personalized audio content based on their emotions. The system mainly consists of a user's terminal, a cloud server, an audio generation engine, an emotion analysis engine, and an audio effect generation module.

[0574] The user's device is responsible for inputting electronic information and sending the analysis results of that information to the cloud server. The device includes a camera and microphone, which are used to collect the user's facial expressions and voice tone in real time and send the user's emotional state to the cloud server.

[0575] The server utilizes computing resources in the cloud to analyze input text data and estimate the character's emotional state. This analysis employs natural language processing techniques and AI-based emotion estimation algorithms. Specifically, the Microsoft Azure Emotion API or equivalent software is used for emotion analysis.

[0576] Based on the estimated emotional state, the speech generation engine selects an appropriate speech model and generates the speech. APIs such as the Google Text-to-Speech API are useful for speech generation, allowing for a variety of voice tones and intonations.

[0577] Furthermore, to automatically generate sound effects appropriate to the situation, sound effect libraries such as FMOD are used. This enhances the acoustic elements to match the scene setting, resulting in a deeper sense of immersion.

[0578] As a concrete example, consider a scenario where a user wants to listen to an audio version of the adventure novel "The Wizard's Journey" while on a crowded train. Based on the user's input on their device, the server adjusts the audio tone to one that promotes relaxation. This allows the user to comfortably enjoy the story without feeling tired, even in the confined space of a train.

[0579] Examples of prompt statements include the following:

[0580] "Upload the text for 'The Wizard's Journey,' and if the user's emotions are fatigued, generate audio content by adding a calming voice and soothing music."

[0581] This makes it possible for the present invention to achieve a high level of personalization that adapts to the user's emotional state and to provide a rich entertainment experience.

[0582] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0583] Step 1:

[0584] The user's device inputs electronic information. The user selects desired content, and the device's camera and microphone collect facial expressions and voice tone. This collected data is sent to the server as input data used for subsequent sentiment analysis.

[0585] Step 2:

[0586] The server analyzes the electronic information received from the user. It uses natural language processing techniques to analyze text data and estimate the emotional state of the character. In this process, for example, a generative AI model is used to detect the emotional flags in the text, and the emotional information related to the text is output as an analysis result.

[0587] Step 3:

[0588] The server analyzes the user's emotional state. It inputs the received real-time facial expression data and voice tone into an emotion analysis engine to estimate the user's current emotional state. The primary tool used here is an emotion analysis library (e.g., Microsoft Azure Emotion API), which outputs emotional characteristics (e.g., relaxed, excited, tired, etc.).

[0589] Step 4:

[0590] The server generates speech based on the character's and the user's emotional state. It selects a voice model with a voice tone corresponding to the estimated emotion and generates the speech using the Google Text-to-Speech API. The generated speech data is the output of the step.

[0591] Step 5:

[0592] The server selects and generates sound effects. It requests sound effects appropriate to the situation from libraries such as the FMOD library, generating sound data that complements the atmosphere of the scene. This results in output sound effect files that provide a rich audio experience.

[0593] Step 6:

[0594] The server combines the generated audio and sound effects to create the final audio content. Using audio editing tools, the audio data and sound effects are adjusted and combined along the timeline, and output as the final content file.

[0595] Step 7:

[0596] The server sends the completed audio content to the user's device. It adjusts the content for smooth streaming playback and then provides it to the user. The user experiences the personalized audio content through their smartphone.

[0597] In this way, the system realizes a system that provides personalized audio content that reflects the user's emotional state through each step.

[0598] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0599] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0600] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0601] [Fourth Embodiment]

[0602] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0603] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0604] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0605] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0606] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0607] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0608] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0609] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0610] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0611] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0612] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0613] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0614] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0615] This invention is a system that takes electronic content as input and converts it into audio content. It begins with the user selecting electronic content via a terminal and uploading it to a server. The server analyzes the text data from the received content and detects the character's emotional state. Based on this detected emotional information, the optimal voice actor model is selected, and appropriate audio is generated.

[0616] Furthermore, the server takes scene descriptions into account and automatically generates necessary sound effects. For example, in a rain scene, it adds rain sounds. These sound effects and audio tracks are combined on the server side to generate integrated audio content. In this generation process, it is also possible to generate audio in a language specified by the user to support multiple languages.

[0617] As a concrete example, suppose a user inputs an e-comic titled "The Adventurer's Story." The server analyzes the story's text and detects scenes where the characters' emotions are heightened. In these scenes, it generates voices that mimic energetic voices, and if it's a battle scene, it adds sound effects of swords and shields. Through this process, the user can experience the story as more immersive audio content. This embodiment of the invention is designed to enable fast, low-cost, and high-quality output.

[0618] The following describes the processing flow.

[0619] Step 1:

[0620] The user uses their device to select an electronic content file and begin uploading it to the server.

[0621] Step 2:

[0622] The terminal sends the selected electronic content to the server, which then checks the format of the received file. If the file format is inappropriate, an error message is sent to the user.

[0623] Step 3:

[0624] The server analyzes the electronic content in the appropriate format and prepares to separate text data and image data page by page.

[0625] Step 4:

[0626] The server uses natural language processing technology to extract character dialogue from text data and performs emotion analysis. As a result, the character's emotional state is estimated.

[0627] Step 5:

[0628] The server selects an appropriate voice actor model based on the emotion analysis results and generates audio data for the lines. The generated audio data is then matched to each line of dialogue spoken by the character.

[0629] Step 6:

[0630] The server analyzes the image data scene and selects appropriate sound effects from a predefined sound effects library. In some cases, sound effects may be automatically generated based on the scene's depiction.

[0631] Step 7:

[0632] The server integrates the generated audio data and sound effect tracks, and adjusts the overall audio track.

[0633] Step 8:

[0634] The server generates a download link for the completed audio content and notifies the user's device.

[0635] (Example 1)

[0636] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0637] When playing electronic content with sound, conventional systems often require manual effort to generate emotionally appropriate voices and add sound effects appropriate to the scene, which is time-consuming. Furthermore, there are limitations in multilingual support and the addition of individual sound effects, resulting in insufficient usability and a poor overall user experience.

[0638] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0639] In this invention, the server includes means for receiving information data as input and analyzing the text data within the information to estimate the emotional state of a character; means for selecting an appropriate voice from a pre-prepared voice model based on the estimated emotional state and generating the voice; and means for automatically generating sound effects corresponding to the scene description and combining them with the generated voice. This makes it possible to automatically and efficiently generate information with voice that corresponds to the emotions and scenes of the content input by the user.

[0640] "Information data" is a general term for digital information such as text, images, and audio data that is stored, processed, communicated, or displayed in electronic format.

[0641] "Text data" refers to information represented as a string of characters, and is digital data that includes sentences, words, and symbols.

[0642] "Character's emotional state" refers to the result of estimating the psychological or emotional state exhibited by a character within text data through analysis.

[0643] A "speech model" is the underlying data or algorithm for speech synthesis technology, designed to mimic specific speech characteristics or voice qualities.

[0644] "Scene description" refers to any description that visually or audibly represents a scene or environment presented within information data.

[0645] "Sound effects" are acoustic elements added to audio information for the purpose of enhancing realism or atmosphere.

[0646] A "user-specified instruction" is a string of characters or a command used to execute an operation or instruction entered by the user into the system.

[0647] "Information with audio" refers to information that includes audio data, making it accessible not only visually but also aurally.

[0648] This invention provides a system for playing electronic information with sound. This system consists of components such as a user, a terminal, and a server, and each component works in coordination to enable efficient content generation.

[0649] The user first uses their device to select the source data for the audio content and uploads this data to the server. This process uses a standard file selection interface and handles various digital content formats, including text files, ebooks, and digital comics. The user's selected data is securely stored in the server's database and then moves on to the next processing stage.

[0650] Upon receiving uploaded data, the server first uses natural language processing (NLP) techniques to analyze the text data. This analysis process utilizes a generative AI model to estimate the emotional state of each character. The server employs state-of-the-art machine learning algorithms and datasets to achieve more accurate emotion detection.

[0651] After the emotional state is detected, the server selects the appropriate voice model from several options and synthesizes the speech. High-resolution speech synthesis software is used for this process, enabling natural and emotionally responsive speech expression.

[0652] Furthermore, the server generates sound effects based on the scene description in the information data and combines the audio track and the sound effect track. It utilizes a sound effects library to automatically generate and add rain sounds, for example, according to a prompt such as "rain scene."

[0653] The system supports multilingual information data, and the server generates audio appropriate for each language based on the information specified by the user. The final generated audio information is provided to the user's device in a format that can be redownloaded. Users can play the content and enjoy the information both visually and aurally.

[0654] As a concrete example, a user inputs an e-comic titled "The Adventurer's Story," and the server uses the prompt "Analyze the emotions in this text, generate audio using an appropriate voice model, and add sound effects appropriate to the scene" to analyze the context of the story. This example allows the user to experience the story in a more immersive way.

[0655] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0656] Step 1:

[0657] The user selects the information data they wish to convert to audio via their device and uploads it to the server. This process utilizes a standard file selection screen to send the information data to the specified upload location on the server. The input is the information data, and the output is the saving of the data to the server.

[0658] Step 2:

[0659] The server receives the information data and analyzes the text data using natural language processing (NLP) techniques. Based on this analysis, it estimates the emotional state of the characters within the text. The input is the uploaded text data, and the output is the analyzed emotional state data. A generative AI model is used for the analysis.

[0660] Step 3:

[0661] The server selects the optimal voice from multiple voice models based on the estimated emotional state and performs speech synthesis. The input is emotional state data and a voice model, and the output is voice data that matches the emotion. Realistic voice expression is achieved through a generative AI model.

[0662] Step 4:

[0663] The server automatically generates sound effects based on the scene description in the information data and combines them with the previously generated audio data. The input is the scene information and the audio synthesis result from the information data, and the output is the integrated information data with audio. Specifically, prompt statements are used, including instructions such as "Add rain sounds in rain scenes."

[0664] Step 5:

[0665] The server generates the final audio-enhanced information data and exports it in the format specified by the user. At this stage, the user receives the content in a format that can be redownloaded. The input is the integrated audio data generated in step 4, and the output is the audio-enhanced file available to the user.

[0666] (Application Example 1)

[0667] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0668] In modern digital content consumption, there is a need for easy ways for users to obtain immersive audio experiences. However, existing technologies make it difficult to quickly and cost-effectively generate voices that respond to emotions and scenes, and to adjust sound effects based on individual user requests. As a result, there is a challenge in realizing sophisticated audio content experiences through personal smart devices.

[0669] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0670] In this invention, the server includes means for receiving electronic content as input and analyzing the text data within the content to estimate the emotional state of a character; means for selecting an appropriate voice from a pre-prepared voice synthesis model based on the estimated emotional state and generating the voice; and means for automatically generating sound effects corresponding to the depiction of the scene and integrating them with the generated voice. This makes it possible for users to quickly and inexpensively enjoy a high-quality, immersive digital content experience with sound using communication devices.

[0671] "Electronic content" refers to digital information media that users can acquire, store, and view via computers and communication devices.

[0672] "Character data" refers to information composed of characters and symbols that is processed, analyzed, and displayed electronically.

[0673] "Character emotional state" refers to information that indicates the psychological situation and emotions expressed by characters within a story or content.

[0674] A "speech synthesis model" is a computer program or algorithm used to convert text data into speech data.

[0675] "Scene description" refers to descriptions or visual representations used to explain a specific place, time, or situation in a story or content.

[0676] "Sound effects" are audio elements added to audiovisual media to emphasize a particular atmosphere or event.

[0677] "Communication equipment" refers to electronic devices used to send and receive information such as voice, data, and video between subscribers.

[0678] "Digital content with audio" refers to digital information media that are distributed or stored with added audio information.

[0679] The system for implementing this invention mainly consists of a server and a user's terminal. The user uploads electronic content from the terminal to the server using a communication device. The server extracts text data from the received electronic content and estimates the character's emotional state using a natural language processing library. Specifically, libraries such as SpaCy and NLTK are used for this purpose. Based on the emotional state, an appropriate voice is generated using a speech synthesis library (e.g., Google Text-to-Speech API).

[0680] Furthermore, the server generates sound effects appropriate to each scene. These sound effects are intended to artificially complement the depiction of a particular scene and refer to a pre-created sound effects library. These sound effects are dynamically customized by a generating AI model and used to enhance the atmosphere of the scene.

[0681] Finally, the server integrates the audio and sound effects to generate digital content with sound. This process allows users to have a more immersive audio experience. For example, if a story called "The Hero's Adventure" is uploaded to the server, the adventure scenes can be reproduced with sounds such as sword swings and footsteps, along with voiceovers that emphasize positive emotions.

[0682] An example of an input prompt for a generative AI model is: "Based on the analyzed text data, please voice the story in a voice that matches the character's emotions. Please add sound effects to the following scene: {scene details}"

[0683] Thus, the present invention can provide users with a rich audio content experience quickly and at low cost by integrating voice generation and sound effects.

[0684] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0685] Step 1:

[0686] The user selects electronic content using a terminal and uploads it to the server. The input in this step is the electronic content, and the output is the server receiving the content. The user operates a communication device to send the target content file through the server's designated upload interface.

[0687] Step 2:

[0688] The server extracts text data from the received electronic content. The input for this step is the uploaded electronic content, and the output is the extracted text data for analysis. The server filters the text information within the content, extracting and organizing character dialogue and explanations.

[0689] Step 3:

[0690] The server analyzes text data to estimate the character's emotional state. The input for this step is the extracted text data, and the output is the estimated emotional state. The server uses a natural language processing library (e.g., SpaCy) to evaluate the emotion from the context and classify it into categories such as "anger" or "joy."

[0691] Step 4:

[0692] The server selects a speech synthesis model based on the estimated emotional state and generates speech. The input for this step is the emotional state and text data, and the output is the generated speech data. The server selects a speech synthesis model appropriate for the emotion and uses the generative AI model to convert the input text into speech.

[0693] Step 5:

[0694] The server generates sound effects corresponding to the scene's depiction and integrates them with the generated audio. The input for this step is scene details and audio data, and the output is integrated digital content with audio. The server selects appropriate sounds from a sound effects library and synthesizes them with the audio data, timing them correctly.

[0695] Step 6:

[0696] The server outputs the generated digital content with audio to the user's terminal. The input for this step is integrated digital content with audio, and the output is an audio file or streaming data that the user can listen to. The user can then enjoy an immersive audio experience through their terminal.

[0697] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0698] This invention provides a system that personalizes the conversion of electronic content into audio content while taking user emotions into consideration. The process begins with the user selecting electronic content via a terminal and uploading it to a server. The server analyzes the text data of the received content and estimates the emotional state of the characters. Based on this estimation, it selects a voice actor model and generates the voice. Furthermore, it generates sound effects corresponding to the scene's depiction, and by combining these, the completed audio content is produced.

[0699] A key feature of this invention is that the server can also consider the user's emotional state. The terminal collects user emotional data in real time and transmits it to the server. The emotion engine analyzes the user's emotions, and for example, if the user is relaxed, it adjusts the voice tone gently to improve the user experience. It is also possible to dynamically adjust content generation in response to changes in the user's emotions.

[0700] For example, suppose a user inputs electronic content of a story called "Magical Adventure." The server analyzes the story's text and estimates the emotions expressed in the main characters' lines. During this process, the terminal collects emotional data from the user's facial expressions, which is then analyzed by an emotion engine. If the server determines that the user is excited, it adjusts the audio content by adding a more forceful intonation. In this way, the user can experience more personalized audio content. Embodiments of the present invention make it possible to provide a rich entertainment experience that is personalized according to the user's emotional state.

[0701] The following describes the processing flow.

[0702] Step 1:

[0703] The user uses their device to select the electronic content files they want to convert and then starts uploading them to the server.

[0704] Step 2:

[0705] The device transmits electronic content to the server. Simultaneously, the device collects emotional data in real time, such as the user's facial expressions and tone of voice, and transmits this data to the server.

[0706] Step 3:

[0707] The server checks the format of the received electronic content and determines whether it is in a valid format. If the format is inappropriate, it notifies the user of an error message via the terminal.

[0708] Step 4:

[0709] The server analyzes the text data of the electronic content and uses natural language processing to extract the characters' lines and emotional states.

[0710] Step 5:

[0711] The emotion engine analyzes user emotion data received in real time and estimates the user's current emotional state. The results are then provided to the server.

[0712] Step 6:

[0713] The server combines the character's emotional state with the estimated user's emotional state to select the optimal voice actor model and generate audio data. It adjusts the tone and speed of the voice as needed.

[0714] Step 7:

[0715] The server selects sound effects based on the scene content, combines the generated audio data with the sound effects, and creates an audio track. During this process, the overall balance is adjusted, taking into account the user's emotions.

[0716] Step 8:

[0717] The server outputs the generated audio content and provides a download link to the device. The user can then view the resulting content on their device.

[0718] (Example 2)

[0719] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0720] In the modern age, electronic data functions as a diverse source of information, but a problem is that text-based information alone cannot fully evoke emotional immersion in users. Furthermore, existing audio content generation systems struggle to provide personalized experiences that reflect each user's emotional state.

[0721] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0722] In this invention, the server includes means for receiving electronic data as input and analyzing the text information within the data to estimate the emotional state of a character; means for acquiring the user's emotional state using a sensor device and reflecting it in voice generation; and means for automatically generating sound corresponding to the situation of the scene and integrating it with the generated voice. This makes it possible to generate personalized voice content that matches the user's emotions.

[0723] "Electronic data" refers to information such as text, images, and audio that is represented in a digital format.

[0724] "Text information" refers to information composed of characters and phrases within electronic data.

[0725] "Character emotional state" refers to the psychological state and emotional expression of the characters or beings that appear in the story or content.

[0726] A "speech synthesis model" is a system or algorithm used to artificially generate human speech based on input data.

[0727] "Acoustics" refers to sounds or sound effects that can be perceived by hearing, and are generated to suit the context.

[0728] A "sensor device" refers to a device that detects physical or chemical properties and outputs them as electrical signals.

[0729] "Speech generation" is the process of creating speech that is understandable to the listener using electronic data and models.

[0730] A "scene" refers to a specific place or setting in which a story or situation unfolds.

[0731] This invention is a system that converts electronic data into audio data using a user's terminal, a server, and a generative AI model. The user first uses their terminal to select the electronic data they want to convert to audio and uploads it to the server. The server analyzes the received text information using natural language processing software. Open-source natural language processing libraries can be used for this analysis. The server then uses an emotion analysis model to estimate the emotional state of a character based on the analysis results.

[0732] Next, the server selects a speech synthesis model and uses it to generate sounds appropriate to the character's emotional state and the situation. This involves using a deep learning model to generate human speech from text. During speech generation, the AI ​​model also automatically generates sound effects appropriate to the situation, and these sound effects are integrated with the speech.

[0733] Furthermore, to enhance the user's individual experience, the device uses sensor devices to measure the user's emotional state in real time and transmits this data to a server. The server analyzes the user's emotional data to reflect the individual's emotional state in the generated audio data.

[0734] As a concrete example, consider a scenario where a user inputs a fantasy adventure story as electronic data. The server analyzes the story's text, estimates the characters' emotions, and then generates appropriate voices. If the emotional data indicates that the user is excited, the server adjusts the voice by adding a stronger intonation.

[0735] Examples of prompts include, "Voice the characters in this fantasy adventure story in a calm voice tone appropriate for when the user is relaxed," and "Generate audio content with a strong intonation to match the user's level of excitement."

[0736] In this way, the system can generate personalized voice data that responds to the user's emotions, providing a rich experience.

[0737] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0738] Step 1:

[0739] The user selects the electronic data they want to convert to audio using a terminal. Electronic data (e.g., text-based stories or documents) is required as input. The terminal prepares the selected data and gets ready to upload it to the server. Throughout this process, the user can operate intuitively via a graphical user interface (GUI).

[0740] Step 2:

[0741] The server receives electronic data uploaded from the terminal. The input is the electronic data itself. The server uses natural language processing software to analyze the text information within the data and extract character dialogue and scene interpretations. This analysis process efficiently identifies the constituent elements within the data and builds a foundation for estimating emotional states.

[0742] Step 3:

[0743] The server estimates the emotional state of the characters based on the analyzed text information. The input is the text analysis results from the previous step. Using an emotion analysis model, the emotions embedded in each line of dialogue are quantified, and a voice actor model is selected based on this information. The output is estimated emotion data corresponding to each character.

[0744] Step 4:

[0745] The server generates voice using the selected voice actor model. The input is the emotion data estimated in step 3. The speech synthesis model generates voice data that matches the character's emotions and tone. The generated voice is adjusted to be realistic and expressive.

[0746] Step 5:

[0747] The server generates sound corresponding to the scenes in the story. The input is information about the scenes in the story. A generative AI model creates sound effects appropriate for each scene and integrates them with the audio data. The output of this step is comprehensive audio data that combines the audio and sound effects.

[0748] Step 6:

[0749] The device collects the user's emotional state using sensor devices. Inputs include the user's facial expressions and biometric information. The device analyzes this data and transmits it to the server in real time. Outputs are numerical data representing the user's emotional state.

[0750] Step 7:

[0751] The server analyzes the user's emotional data and incorporates it into the generated audio data. The input is the user emotional data obtained in step 6. The tone and tempo of the audio are adjusted to match the user's state. This makes it possible to provide the user with a personalized experience.

[0752] Step 8:

[0753] The server sends the adjusted audio data to the device. The final output is personalized audio electronic data tailored to the user's emotions. The user can play it on their device and enjoy emotionally rich content.

[0754] (Application Example 2)

[0755] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0756] In recent years, there has been a growing demand for personalized audio content that adapts to users' emotions. However, conventional audio generation systems have been insufficient in adjusting audio to take into account the user's emotional state, making it difficult to provide a personalized experience. Furthermore, there is a lack of systems that support multiple languages ​​and have the flexibility to add sound effects individually to specific scenes. As a result, there is a challenge in that the personalized experience for users is limited.

[0757] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0758] In this invention, the server includes means for receiving electronic information as input and analyzing the text data within the information to estimate the emotional state of a character; means for recognizing the emotional state of the user and adjusting the voice tone based on that recognition; and means for enabling the addition of sound effects individually for specific situations specified by the user. This makes it possible to personalize audio content according to the user's emotions and provide a richer entertainment experience.

[0759] "Electronic information" refers to all data stored or transmitted in digital format, and specifically includes formats such as text, audio, images, and video.

[0760] "Text data" refers to a collection of string information that makes up a document, and is the subject of analysis using natural language processing and other methods.

[0761] "Character emotional state" refers to the emotions expressed by the characters appearing in the text, and specifically includes psychological states such as joy, anger, sadness, and happiness.

[0762] A "voice model" is an algorithm or software for digital speech synthesis that imitates specific voice characteristics or timbre.

[0763] "Sound effects" are audio elements added to visual or audio content to emphasize specific scenes or emotions.

[0764] "User emotional state" refers to the real-time emotional tendencies and psychological state exhibited by the system user, and is inferred from facial expressions, tone of voice, and behavior.

[0765] "Voice tone" refers to the acoustic characteristics of a voice, such as its pitch, strength, and intonation, and is a means of conveying emotions and atmosphere.

[0766] "Personalization" is a concept that refers to the provision of customized experiences and services based on the specific needs and preferences of individual users.

[0767] This invention relates to a system that provides users with personalized audio content based on their emotions. The system mainly consists of a user's terminal, a cloud server, an audio generation engine, an emotion analysis engine, and an audio effect generation module.

[0768] The user's device is responsible for inputting electronic information and sending the analysis results of that information to the cloud server. The device includes a camera and microphone, which are used to collect the user's facial expressions and voice tone in real time and send the user's emotional state to the cloud server.

[0769] The server utilizes computing resources in the cloud to analyze input text data and estimate the character's emotional state. This analysis employs natural language processing techniques and AI-based emotion estimation algorithms. Specifically, the Microsoft Azure Emotion API or equivalent software is used for emotion analysis.

[0770] Based on the estimated emotional state, the speech generation engine selects an appropriate speech model and generates the speech. APIs such as the Google Text-to-Speech API are useful for speech generation, allowing for a variety of voice tones and intonations.

[0771] Furthermore, to automatically generate sound effects appropriate to the situation, sound effect libraries such as FMOD are used. This enhances the acoustic elements to match the scene setting, resulting in a deeper sense of immersion.

[0772] As a concrete example, consider a scenario where a user wants to listen to an audio version of the adventure novel "The Wizard's Journey" while on a crowded train. Based on the user's input on their device, the server adjusts the audio tone to one that promotes relaxation. This allows the user to comfortably enjoy the story without feeling tired, even in the confined space of a train.

[0773] Examples of prompt statements include the following:

[0774] "Upload the text for 'The Wizard's Journey,' and if the user's emotions are fatigued, generate audio content by adding a calming voice and soothing music."

[0775] This makes it possible for the present invention to achieve a high level of personalization that adapts to the user's emotional state and to provide a rich entertainment experience.

[0776] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0777] Step 1:

[0778] The user's device inputs electronic information. The user selects desired content, and the device's camera and microphone collect facial expressions and voice tone. This collected data is sent to the server as input data used for subsequent sentiment analysis.

[0779] Step 2:

[0780] The server analyzes the electronic information received from the user. It uses natural language processing techniques to analyze text data and estimate the emotional state of the character. In this process, for example, a generative AI model is used to detect the emotional flags in the text, and the emotional information related to the text is output as an analysis result.

[0781] Step 3:

[0782] The server analyzes the user's emotional state. It inputs the received real-time facial expression data and voice tone into an emotion analysis engine to estimate the user's current emotional state. The primary tool used here is an emotion analysis library (e.g., Microsoft Azure Emotion API), which outputs emotional characteristics (e.g., relaxed, excited, tired, etc.).

[0783] Step 4:

[0784] The server generates speech based on the character's and the user's emotional state. It selects a voice model with a voice tone corresponding to the estimated emotion and generates the speech using the Google Text-to-Speech API. The generated speech data is the output of the step.

[0785] Step 5:

[0786] The server selects and generates sound effects. It requests sound effects appropriate to the situation from libraries such as the FMOD library, generating sound data that complements the atmosphere of the scene. This results in output sound effect files that provide a rich audio experience.

[0787] Step 6:

[0788] The server combines the generated audio and sound effects to create the final audio content. Using audio editing tools, the audio data and sound effects are adjusted and combined along the timeline, and output as the final content file.

[0789] Step 7:

[0790] The server sends the completed audio content to the user's device. It adjusts the content for smooth streaming playback and then provides it to the user. The user experiences the personalized audio content through their smartphone.

[0791] In this way, the system realizes a system that provides personalized audio content that reflects the user's emotional state through each step.

[0792] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0793] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0794] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0795] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0796] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0797] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0798] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0799] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0800] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0801] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0802] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0803] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0804] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0805] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0806] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0807] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0808] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0809] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0810] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0811] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0812] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0813] The following is further disclosed regarding the embodiments described above.

[0814] (Claim 1)

[0815] [A means of receiving electronic content as input, analyzing the text data within the content, and estimating the emotional state of a character,

[0816] [A means for selecting an appropriate voice from pre-prepared voice actor models based on an estimated emotional state and generating audio,

[0817] [A means for automatically generating sound effects corresponding to the scene's depiction and combining them with the generated audio,

[0818] [Means for outputting generated audio content,

[0819] A system that includes this.

[0820] (Claim 2)

[0821] [The system according to claim 1, further comprising a function to generate audio corresponding to each language when the input content includes multiple languages.

[0822] (Claim 3)

[0823] The system according to claim 1, further comprising a function that allows the user to individually add sound effects to specific scenes specified by the user.

[0824] "Example 1"

[0825] (Claim 1)

[0826] [A method for receiving information data as input and analyzing the text data within that information to estimate the emotional state of a character,

[0827] [A means for selecting an appropriate voice from a pre-prepared voice model based on an estimated emotional state and generating a voice,

[0828] [Methods for automatically generating sound effects corresponding to the scene description and combining them with the generated audio,

[0829] [Means for controlling voice generation and sound effect addition using user-specified command statements,

[0830] [Means for outputting generated audio information,

[0831] A system that includes this.

[0832] (Claim 2)

[0833] [The system according to claim 1, further comprising a function to generate audio corresponding to each language when the input information includes multiple languages.

[0834] (Claim 3)

[0835] The system according to claim 1, which includes a function that allows the user to individually add sound effects to specific scenes specified by the user.

[0836] "Application Example 1"

[0837] (Claim 1)

[0838] [A means of receiving electronic content as input, analyzing the text data within the content, and estimating the emotional state of a character,

[0839] [Means for selecting an appropriate voice from a pre-prepared speech synthesis model based on an estimated emotional state and generating the voice,

[0840] [Means for automatically generating sound effects corresponding to the scene description and integrating them with the generated audio,

[0841] [Means for outputting generated digital content with audio,

[0842] [Means that enable users to experience content distribution services using communication devices,

[0843] A system that includes this.

[0844] (Claim 2)

[0845] [The system according to claim 1, further comprising a function to generate audio corresponding to each language when the input content includes multiple languages.

[0846] (Claim 3)

[0847] The system according to claim 1, which includes a function that allows the user to individually add sound effects to specific scenes specified by the user.

[0848] "Example 2 of combining an emotion engine"

[0849] (Claim 1)

[0850] [A method for receiving electronic data as input and analyzing the text information within the data to estimate the emotional state of a character,

[0851] [Means for selecting an appropriate voice from a prepared speech synthesis model based on an estimated emotional state and generating the voice,

[0852] [Means for automatically generating sound corresponding to the situation of a scene and integrating it with the generated sound,

[0853] [Methods for acquiring the user's emotional state using a sensor device and reflecting it in voice generation,

[0854] [Means for outputting generated audio data,

[0855] A system that includes this.

[0856] (Claim 2)

[0857] [The system according to claim 1, further comprising a function to generate speech corresponding to each language when the input data includes multiple languages.

[0858] (Claim 3)

[0859] The system according to claim 1, which includes a function that allows the user to individually add sound effects to specific scenes specified by the user.

[0860] "Application example 2 when combining with an emotional engine"

[0861] (Claim 1)

[0862] [A means of receiving electronic information as input and analyzing the text data within that information to estimate the emotional state of a character,

[0863] [A means for selecting an appropriate voice from a pre-prepared voice model based on an estimated emotional state and generating speech,

[0864] [Means for automatically generating sound effects corresponding to the description of the situation and combining them with the generated audio,

[0865] [Means for recognizing the user's emotional state and adjusting the voice tone based on that recognition,

[0866] [Means for outputting generated audio information,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] [The system according to claim 1, further comprising a function to generate audio corresponding to each language when the input information includes multiple languages.

[0870] (Claim 3)

[0871] The system according to claim 1, further comprising a function that enables the addition of individual sound effects for specific situations specified by the user. [Explanation of Symbols]

[0872] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving electronic content as input, analyzing the text data within the content, and estimating the emotional state of a character, A means for selecting an appropriate voice from pre-prepared voice actor models based on an estimated emotional state and generating speech, A means for automatically generating sound effects corresponding to the scene's depiction and combining them with the generated audio, A means for outputting the generated audio content, A system that includes this.

2. The system according to claim 1, further comprising a function to generate audio corresponding to each language when the input content includes multiple languages.

3. The system according to claim 1, further comprising a function that enables the addition of sound effects to specific scenes designated by the user.

Images