Information processing device and information processing method

Abstract

An information processing device (10) comprises: a reception unit (11) that receives generation request information of a music content suitable for a scene; an acquisition unit (12) that acquires information for scene estimation in response to the reception of the generation request information of the music content suitable for the scene; an estimation unit (13) that estimates a scene on the basis of the acquired information for scene estimation; and an output unit (14) that outputs an input sentence to a prompt for indicating generation of the music content on the basis of the estimated scene.

Description

Information processing device and information processing method

[0001] The present disclosure relates to an information processing device and an information processing method.

[0002] In recent years, various types of content have been generated using generative artificial intelligence (AI) models. A generative AI model is a model that can generate content (generation results) in response to a prompt containing input information, according to any one or a combination of instructions, context, questions, and output formats indicated by the prompt, and return the generated content as response information.

[0003] The technology itself for generating music content using the above-described generative AI model already exists (see Patent Document 1).

[0004] Special Publication No. 2023-538411

[0005] On the other hand, in recent years, there has been a demand for a system that estimates a scene based on the surrounding circumstances, user attributes, preferences, etc., and generates music content suited to the estimated scene. However, there has been little research into generating music content suited to such scenes.

[0006] Therefore, the present disclosure aims to utilize a generative AI model to automatically generate music content suitable for a scene estimated from the surrounding circumstances, user attributes and preferences, etc.

[0007] The information processing device of the present disclosure includes a reception unit that receives request information for generating music content suitable for a scene, an acquisition unit that acquires information for scene estimation in response to the reception of the request information for generating the music content, an estimation unit that estimates a scene based on the acquired information for scene estimation, and an output unit that outputs an input sentence to a prompt to instruct the generation of music content based on the estimated scene.

[0008] According to the present disclosure, by utilizing a generative AI model, it is possible to automatically generate music content suitable for a scene estimated from the surrounding circumstances, user attributes and preferences, etc.

[0009] It is a block diagram of an entire system including an information processing device. It is a flow diagram of processing executed by the information processing device. It is a diagram showing an example of information for scene estimation. It is a diagram showing an example of an input sentence to a prompt. It is a diagram showing another system configuration example. It is a diagram showing a hardware configuration example of an information processing device.

[0010] Hereinafter, an embodiment of an information processing device and an information processing method according to the present disclosure will be described with reference to the drawings. In the following embodiment, a form will be described in which a large language model (LLM) that is mainly used for text generation is used as an example of a generative AI model.

[0011] [Configuration of a System Including an Information Processing Device] FIG. 1 shows a configuration diagram of a system 1 including an information processing device 10 according to the present disclosure. As shown in FIG. 1, the system 1 includes an external server 30A running a large-scale language model (LLM) 30, the information processing device 10, and an external server 20A. The external server 20A stores various information, including, for example, a map information database (DB) 20, a music information database (DB) 21, and a user information database (DB) 22. The map information DB 20 stores map information used to estimate a user's current location and activity details. The map information includes, for example, map data for various regions and information on various commercial facilities, event facilities, and buildings. The music information DB 21 stores reference information for generating music content suited to a scene. The reference information includes, for example, information on various musicians, various music genres, and various song specifications (such as melody and length). The user information DB 22 stores various information about users, and the information about users includes, for example, user attribute information (information such as the user's age, gender, family structure, place of residence, occupation, and annual income), and user preference information (information such as favorite music genres (J-pop, techno, anime songs, classical, rock, dance music, etc.), and songs frequently listened to on video distribution sites and music distribution services). The information processing device 10 can employ various information processing devices (smartphones, mobile phones, smartwatches, wearable devices, laptops, desktop computers, servers, etc.) as hardware, but the information processing device 10 of this embodiment is intended to be a mobile device carried by the user (smartphones, mobile phones, smartwatches, wearable devices, etc.).

[0012] An RAG (Retrieval-Augmented Generation) system application is installed on the information processing device 10, and the RAG system operates. The RAG system is a type of prompt extension technology used for corporate information linkage between LLMs. Specifically, when a generation request is made to an LLM using an instruction (input text in response to a prompt) based on a content generation request, the system searches for related information (reference information) in advance if necessary and requests the LLM to generate the content together with the instruction. The present disclosure corresponds to an invention that extends and improves the functionality of the RAG system, and has an aspect of enriching and optimizing the instruction (input text in response to a prompt) for the LLM 30 using various information acquired from a map information DB 20, a music information DB 21, and a user information DB 22. To realize the functions related to the present disclosure, the information processing device 10 includes a receiving unit 11, an acquiring unit 12, an estimating unit 13, and an output unit 14. The functions of each unit are described below.

[0013] The reception unit 11 is a functional unit that receives request information for generating music content suitable for a scene. The request information for generating music content suitable for a scene is notified to the reception unit 11 when a generation request button provided on a web page or an application page displayed on the display of the information processing device 10 is pressed.

[0014] The acquisition unit 12 is a functional unit that acquires information for scene estimation in response to the reception of the music content generation request information. Examples of the "information for scene estimation" include (1) the user's location information, acceleration information, and map information around the current location, (2) user attribute information, (3) user preference information, and (4) selection information individually input by the user. The acquisition unit 12 acquires the user's location information and acceleration information using functions (positioning function and acceleration measurement function) unique to the information processing device 10, which is a mobile terminal. Furthermore, to estimate the user's current location and activity details from the current location information, the acquisition unit 12 searches the map information DB 20 to acquire map information around the current location. The acquisition unit 12 also searches the user information DB 22 using a user ID or other key to acquire user attribute information (e.g., the user's age, gender, family structure, place of residence, occupation, annual income, etc.) and user preference information (e.g., favorite music genres (e.g., J-pop, techno, anime songs, classical, rock, dance music, etc.), songs frequently listened to on video distribution sites and music distribution services, etc.). Furthermore, if there is selection information individually input by the user, the selection information is acquired from the reception unit 11 .

[0015] The estimation unit 13 is a functional unit that estimates a scene based on acquired scene estimation information. In this embodiment, the estimation unit 13 estimates the current location and activity details, which are the basis for estimating the scene, based on the acquired current position information, acceleration information, and map information around the current location. For example, even if the current location is estimated to be a park, the park may contain a running course, tennis courts, a music concert venue, and other facilities, making it difficult to estimate the activity details. In such a case, the estimation unit 13 estimates the user's activity details based on information for scene estimation, such as (2) user attribute information, (3) user preference information, and (4) selection information individually input by the user. The estimation unit 13 then estimates a scene from the current location and activity details. An example of estimating a scene in which a user is running in a park will be described below.

[0016] The output unit 14 is a functional unit that outputs an input sentence (an instruction sentence exemplified in FIG. 4 ) to a prompt for instructing the generation of music content based on the estimated scene. The output unit 14 also receives and outputs the generated music content as a generation result output from the LLM 30 in response to the input sentence to the prompt. The music content can be music data in MP3 format or the like that can be played by a music playback application installed on the information processing device 10.

[0017] In this embodiment, the output unit 14 searches the music information DB 21 of the external server 20A to obtain reference information for generating music content suited to a scene (e.g., information about musicians, music genres, and song specifications (e.g., melody, length, etc.)), and includes the reference information in the input sentence for the prompt. For example, the music information DB 21 may be searched using keywords such as "music to listen to when you're in a mellow mood" to obtain famous hits and their descriptions as the reference information. In this case, expressions such as "soft" or "comfortable" may be used instead of "mellow," or information about genres such as "downtempo," "trip-hop," and "ambient" may be used. Furthermore, feature values ​​may be extracted for each piece of information useful for generating music content (e.g., musical scales, melodies, chords, etc.), and the useful information suited to a scene may be obtained as the reference information using a learning model trained on pre-specified combinations of these feature values ​​and scenes. As a result, the LLM 30 generates music content based on the reference information, and it is expected that the generated music content by the LLM 30 will be more suited to the scene.

[0018] Furthermore, the output unit 14 may include, as the reference information, information indicating the degree of the conditions for generating musical content in the input sentence for the prompt. For example, by including "Techno 70%, J-Pop 30%" in the input sentence as condition (2) shown in FIG. 4, a techno song with J-Pop-like elements can be generated. By including such information indicating the degree, it is possible to instruct the generation of complex musical content that sounds as if it were conceived by a human. Note that the information indicating the degree may be information received from the user or may be determined based on information registered in advance by the operator.

[0019] The output unit 14 may also include in the input sentences for the prompt conditions related to the playback time suited to the scene, the playback volume suited to the scene, etc. In this case, the LLM 30 generates music content based on the above conditions, and as a result of generation by the LLM 30, it can be expected that music content that is more suited to the scene in terms of both playback time and playback volume will be output.

[0020] Alternatively, the output unit 14 may generate multiple candidate music content items and include in the input sentence of the prompt a statement indicating that the music content to be output as the generated result will be selected from the multiple music content items based on the scene. In this case, the LLM 30 generates the music content based on the above instructions, so that the generated result by the LLM 30 can be expected to be music content that matches the scene at that time, and even if the scene changes, music content that matches the new scene can be expected to be quickly output.

[0021] [Processing Executed in Information Processing Device] Hereinafter, processing executed in the information processing device 10 (processing related to the information processing method of the present disclosure) will be described with reference to the flow diagram of FIG. 2 .

[0022] When a user presses a generation request button provided on a web page or application page displayed on the display of the information processing device 10, generation request information for music content appropriate for the scene is notified to the reception unit 11, and the process of Figure 2 begins when the reception unit 11 receives the above generation request information.

[0023] In response to receiving the generation request information, the acquisition unit 12 acquires the information for the scene estimation described above (step S1). For example, the acquisition unit 12 acquires current location information and acceleration information using a positioning function inherent to the mobile terminal, and further, in order to estimate the current location and activity details from the current location information, searches the map information DB 20 of the external server 20A to acquire map information around the current location. Here, for example, the information for scene estimation shown in FIG. 3 is acquired: "User attribute information: Male in his 30s; User preference information: Likes the outdoors; Likes running; Music genre: Favorite music is techno, followed by J-pop; Acquired data: Current location information; Acceleration information; Map information around the current location..."

[0024] Next, the estimation unit 13 estimates a scene based on the information for scene estimation (step S2). For example, the estimation unit 13 compares the user's current location information with map data to estimate that the user's current location is within the grounds of Park A, and also determines the user's movement speed from the temporal transition of the location information, and estimates that the user is running based on the movement speed, acceleration information, and user preference information (e.g., likes running), thereby estimating the scene as "running in Park A."

[0025] Next, the output unit 14 outputs an input sentence (an instruction sentence to the LLM 30) to the prompt for instructing the generation of musical content based on the scene. For example, an input sentence including multiple items such as role, task, and condition, as shown in FIG. 4 , could be: "Role: You are a composer. Task: Please generate musical background music. Conditions (1) Make it up-tempo background music like listening to while running. (2) The genre should be 70% techno and 30% J-pop. (3) The length should be approximately 30 minutes. (4) The playback volume should be high..." As mentioned above, by including information indicating the degree of complexity, such as in the above condition (2) "70% techno and 30% J-pop," it is possible to instruct the generation of complex musical content that seems as if it were conceived by a human (a techno piece with J-pop-like elements).

[0026] Thereafter, the LLM 30 outputs the music content generated based on the scenes as the generation result, and the output unit 14 acquires and outputs the generation result (music content) from the LLM 30 (step S4). Here, for example, music data in MP3 format or the like that can be played by a music playback application installed on the information processing device 10 is acquired as the music content.

[0027] In this way, by utilizing the generative AI model (LLM30), it is possible to automatically generate music content suited to a scene estimated from the surrounding circumstances, user attributes, preferences, etc. The user can then listen to and enjoy music content suited to the current scene (e.g., "running in Park A"). For the user, automatically generating and outputting music content suited to the current scene is extremely useful in situations where the user wants to "listen to any kind of music!"

[0028] (Modification of System 1) System 1 is not limited to the configuration shown in FIG. 1 , and may have a configuration in which LLM 30 is implemented in information processing device 10, as shown in FIG. 5 . This configuration can be realized by installing an application that executes the functions of LLM 30 in information processing device 10. Furthermore, while FIGS. 1 and 5 show examples in which map information DB 20, music information DB 21, and user information DB 22 are implemented outside information processing device 10 (for example, on a network), at least one of these may be implemented inside information processing device 10.

[0029] The gist of the present disclosure lies in the following [1] to [8]. [1] An information processing device comprising: a receiving unit that receives request information for generating musical content suited to a scene; an acquisition unit that acquires information for scene estimation in response to the reception of the request information for generating musical content; an estimation unit that estimates a scene based on the acquired information for scene estimation; and an output unit that outputs an input sentence to a prompt for instructing the generation of musical content based on the estimated scene. [2] The information processing device described in [1], wherein the acquisition unit acquires at least current position information, acceleration information, and map information as the information for scene estimation, and the estimation unit estimates a current location and activity details that serve as a basis for estimating the scene based on at least the position information, the acceleration information, and the map information. [3] The information processing device described in [1] or [2], wherein the output unit includes reference information for generating musical content suited to the scene in the input sentence to the prompt. [4] The information processing device described in [3], wherein the output unit includes information indicating a degree of a condition for generating the musical content as the reference information in the input sentence to the prompt. [5] The information processing device according to any one of [1] to [4], wherein the output unit includes a condition related to a playback time that suits the scene in the sentence input to the prompt. [6] The information processing device according to any one of [1] to [5], wherein the output unit includes a condition related to a playback volume that suits the scene in the sentence input to the prompt. [7] The information processing device according to any one of [1] to [6], wherein the output unit generates a plurality of candidate music contents in advance, and includes in the sentence input to the prompt an indication that a music content to be output as a generation result will be determined from the plurality of music contents based on the scene. [8] The information processing device according to any one of [1] to [7], wherein the output unit receives and outputs generated music content as a generation result output from a generative AI model in response to input of the input sentence to the prompt.[9] An information processing method comprising: a step in which an information processing device receives request information for generating music content suitable for a scene; a step in which the information processing device acquires information for scene estimation in response to the reception of the request information for generating the music content; a step in which the information processing device estimates a scene based on the acquired information for scene estimation; and a step in which the information processing device outputs an input sentence to a prompt for instructing the generation of music content based on the estimated scene.

[0030] [Explanation of Terms, Explanation of Hardware Configuration (FIG. 6), etc.] The block diagrams used in the description of the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (e.g., wired, wireless, etc.) and these multiple devices. The functional block may also be realized by combining software with the single device or multiple devices.

[0031] Functions include, but are not limited to, judgment, determination, assessment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0032] For example, an information processing device according to an embodiment of the present disclosure may function as a computer that executes the processes of the present disclosure. Fig. 6 is a diagram illustrating an example of a hardware configuration of an information processing device 10 according to an embodiment of the present disclosure. The information processing device 10 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0033] In the following description, the term "apparatus" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the information processing device 10 may be configured to include one or more of the apparatuses shown in the drawings, or may be configured to exclude some of the apparatuses.

[0034] Each function of the information processing device 10 is realized by loading specified software (programs) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations, control communication via the communication device 1004, and control at least one of reading and writing data in the memory 1002 and storage 1003.

[0035] The processor 1001 controls the entire computer by running, for example, an operating system, and may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc.

[0036] The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002 and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above-described embodiments. While the various processes have been described as being executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The programs may be transmitted from a network via a telecommunications line.

[0037] The memory 1002 is a computer-readable recording medium and may be configured by, for example, at least one of a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to an embodiment of the present disclosure.

[0038] Storage 1003 is a computer-readable recording medium, and may be composed of at least one of, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, a server, or other appropriate medium including at least one of memory 1002 and storage 1003.

[0039] The communication device 1004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, etc. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. to realize at least one of frequency division duplex (FDD) and time division duplex (TDD).

[0040] The input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device 1006 is an output device (e.g., a display, a speaker, an LED lamp, etc.) that outputs to the outside. The input device 1005 and the output device 1006 may be integrated into one device (e.g., a touch panel).

[0041] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.

[0042] The information processing device 10 may also be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0043] The notification of information is not limited to the aspects / embodiments described in the present disclosure and may be performed using other methods. For example, the notification of information may be performed by physical layer signaling (e.g., Downlink Control Information (DCI) and Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information (Master Information Block (MIB) and System Information Block (SIB))), other signals, or a combination thereof. Furthermore, the RRC signaling may be referred to as an RRC message, and may be, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, or the like.

[0044] Each aspect / embodiment described in the present disclosure may be implemented using any of the following standards: LTE (Long Term Evolution), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), 6th generation mobile communication system (6G), xth generation mobile communication system (xG) (xG (x is, for example, an integer or a decimal number)), FRA (Future Radio Access), NR (new Radio), New radio access (NX), Future generation radio access (FX), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.17 (WiMAX (registered trademark)), IEEE 802.19 (WiMAX (registered trademark)), IEEE 802.20 (WiMAX (registered trademark)), IEEE 802.21 (Wi-Fi (registered trademark)), IEEE 802.22 (WiMAX (registered trademark)), IEEE 802.23 (WiMAX (registered trademark)), IEEE 802.24 (WiMAX (registered trademark)), IEEE 802.25 (WiMAX (registered trademark)), IEEE 802.26 (WiMAX (registered trademark)), IEEE 802.27 (WiMAX (registered trademark)), IEEE 802.28 (WiMAX (registered trademark)), IEEE 802.29 (WiMAX (registered trademark)), IEEE 802.30 (WiMAX (registered trademark)), IEEE 802.31 (Wi-Fi (registered trademark)), IEEE 802.32 (WiMAX (registered trademark)), IEEE 802.33 (WiMAX (registered trademark)), IEEE 802.34 ( The present invention may be applied to at least one of systems using 802.20, Ultra-Wideband (UWB), Bluetooth, or other suitable systems, and next-generation systems that are extended, modified, created, or defined based on these systems. It may also be applied to a combination of multiple systems (e.g., a combination of LTE and / or LTE-A with 5G).

[0045] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0046] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

[0047] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0048] The aspects / embodiments described in this disclosure may be used alone, in combination, or switched depending on the implementation. Notification of predetermined information (e.g., notification that "X is true") is not limited to explicit notification, but may be implicit (e.g., not notifying the predetermined information).

[0049] Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

[0050] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0051] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then these wired and / or wireless technologies are included within the definition of transmission media.

[0052] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0053] Note that terms described in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of a channel and a symbol may be a signal (signaling). Furthermore, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, a cell, a frequency carrier, etc.

[0054] As used in this disclosure, the terms "system" and "network" are used interchangeably.

[0055] Furthermore, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information. For example, a radio resource may be indicated by an index.

[0056] The names used for the above-described parameters are not intended to be limiting in any way. Furthermore, the mathematical expressions using these parameters may differ from those explicitly disclosed in this disclosure. The various channels (e.g., PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not intended to be limiting in any way.

[0057] As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching in a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like. Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judged" or "decided." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0058] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0059] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0060] When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, when the term "or" is used in this disclosure, it is not intended to be an exclusive or.

[0061] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0062] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different."

[0063] 1...system, 10...information processing device, 11...reception unit, 12...acquisition unit, 13...estimation unit, 14...output unit, 20...map information DB, 21...music information DB, 22...user information DB, 20A, 30A...external server, 30...LLM, 1001...processor, 1002...memory, 1003...storage, 1004...communication device, 1005...input device, 1006...output device, 1007...bus.

Claims

1. An information processing device comprising: a reception unit that receives request information for generating music content suitable for a scene; an acquisition unit that acquires information for scene estimation in response to the reception of the request information for generating the music content; an estimation unit that estimates a scene based on the acquired information for scene estimation; and an output unit that outputs an input sentence to a prompt for instructing the generation of music content based on the estimated scene.

2. The information processing device of claim 1, wherein the acquisition unit acquires at least current location information, acceleration information, and map information as information for the scene estimation, and the estimation unit estimates the current location and activity content that serve as the basis for estimating the scene based on at least the location information, the acceleration information, and the map information.

3. The information processing device according to claim 1, wherein the output unit includes reference information for generating music content suited to the scene in the input sentence for the prompt.

4. The information processing device according to claim 3, wherein the output unit includes, as the reference information, information indicating the degree of the conditions for generating the music content in the input sentence for the prompt.

5. The information processing device according to claim 1, wherein the output unit includes a condition regarding a playback time suitable for the scene in the input sentence for the prompt.

6. The information processing device according to claim 1, wherein the output unit includes a condition regarding a playback volume suited to the scene in the input sentence for the prompt.

7. The information processing device according to claim 1, wherein the output unit generates a plurality of candidate music contents in advance, and includes in the input sentence to the prompt a statement that the music content to be output as the generated result will be determined from the plurality of music contents based on the scene.

8. The information processing device according to claim 1, wherein the output unit receives and outputs generated music content as a generation result output from a generative AI model in response to input of the input sentence to the prompt.

9. An information processing method comprising: a step in which an information processing device receives request information for generating music content suitable for a scene; a step in which the information processing device acquires information for scene estimation in response to receiving the request information for generating music content; a step in which the information processing device estimates a scene based on the acquired information for scene estimation; and a step in which the information processing device outputs an input sentence to a prompt for instructing the generation of music content based on the estimated scene.