37 results about "Emoticon" patented technology

An artificial intelligence-driven sentiment analysis system for social media monitoring, comprising: a data collection module configured to retrieve user-generated content from at least one social media platform via application programming interfaces (APIs); a preprocessing module configured to process and clean the collected data by removing irrelevant content, tokenizing the text, removing stop words, and assigning sentiment indicators to emojis, slang, and abbreviations; a sentiment analysis engine comprising one or more deep learning models, wherein the deep learning models include recurrent neural networks (RNNs), long-short-term memory networks (LSTM), and transformer-based models configured to analyze the preprocessed data and classify the content into one or more sentiment categories; an emotion recognition module configured to detect emotional tones within the content and classify them into predefined emotional categories; a real-time data processing unit configured to continuously monitor social media content and provide real-time insights into moods and emotions; a feedback loop module configured to update and refine the deep learning models through reinforcement learning based on new data inputs and sentiment classification results; and a user interface module configured to visualize sentiment and emotion analysis results in real time, including heatmaps, sentiment trend analysis, and emotional breakdowns.

The invention discloses an emotion expression method and device, equipment and a computer readable storage medium. The method comprises the following steps: acquiring first session information input to a robot by a first user; generating second session information output to the first user by the robot according to the first session information; the second session information comprises a first emoticon; determining a first emotion label and / or first emotion intensity corresponding to the first emotion icon; the robot is controlled to output a first emotion related behavior corresponding to the first emotion label and / or the first emotion intensity, the first emotion related behavior comprises at least one of outputting corresponding voice interaction information, outputting a corresponding expression and executing a corresponding action, and the voice interaction information is included in the second session information.

The invention discloses a data search method and device, a product and equipment, and the method comprises the steps: obtaining a search text which is used for triggering the search of an emoticon; intention recognition is conducted on the search text from N intention understanding dimensions, N intention texts of the search text are generated, one intention text corresponds to one intention understanding dimension, and N is a positive integer; obtaining a text label of each emoticon in an emoticon library, wherein the text label of any emoticon comprises intention labels of any emoticon on N intention understanding dimensions; and searching a matched first emoticon for the search text in the emoticon library according to the similarity between the N intention texts and the text labels of the emoticons in the emoticon library. By adopting the method and the device, the accuracy of searching the emoticon matched with the search text in the emoticon library can be improved.

The invention relates to a time domain secondary sentiment analysis method and system based on text symbolization. According to the method, an expression label library and a Chinese vocabulary library are constructed, text data are subjected to preprocessing, encoding and sequence filling processing, a deep learning model is combined with a time domain secondary screening mechanism to mine potential emotions, and meanwhile, emotion inflection points are tracked and subjected to labeling storage; the technical problems of single-dimensional analysis, lack of dynamic monitoring ability and insufficient emoticon utilization in the existing emotion analysis technology are solved, multi-dimensional, dynamic and refined emotion analysis is achieved, the precision, depth and early warning ability of emotion analysis are remarkably improved, and the emotion analysis efficiency is improved. And meanwhile, the technical effects of traceability and expandability of the system are enhanced.

This invention relates to the field of artificial intelligence processing, specifically to a method for generating non-functional interactive personalized random input, comprising the following steps: S1, basic data collection; S2, personalized random input generation; S3, output of generated content and reception of interactive feedback; S4, emotional feature fusion and extraction, obtaining surface emotional features and scene emotional features and performing emotional feature fusion; S5, lightweight emotional classification and multimodal response scheduling; S6, emotional response output, simultaneously outputting text, emoticons, and voice resources to the user; S7, quantitative analysis of user interaction willingness; S8, dynamic threshold iteration and adjustment of interaction intensity; S9, cross-stage data reuse and full-link reverse iteration, solving the problems of insufficient content generation adaptability, insufficient accuracy and real-time performance of emotional responses, and inefficient interaction links and adjustment mechanisms in traditional technologies in terms of underlying algorithms, model architecture, and technical mechanisms.

The invention provides a face recognition-based head portrait generation method, system and device, and a storage medium. The method comprises the steps of collecting head portrait data of a user; generating at least one expression package based on the head portrait data of the user, the expression package including a plurality of expression head portraits representing the emotion of the user, and taking the selected expression head portrait as a default head portrait of the user; identifying current head portrait data of the user when the user logs in, performing expression identification, and taking an expression head portrait corresponding to the current expression of the user as a current head portrait of the user; and displaying the current head portrait to at least one user permitted by the user. According to the method, a series of expression packages representing different emotions can be generated based on the head portrait data of the user, the personalized customized expressions can enrich the interaction means of the user, the functionality of the head portrait of the user can be improved, and the interaction experience between the users is enhanced.

1. Name of this design: Interactive area for generating, displaying, and interacting with popular meme-related emoticons in a graphical user interface for electronic devices. 2. Purpose of this design product: an electronic device. 3. The key design features of this product are: the parts in the graphical user interface, and the parts not marked with dotted lines are the parts for which protection is required. 4. The picture or photo that best illustrates the key points of the design: Main view of Design 1. 5. Designate Design 1 as the base design. 6. Purpose of the graphical user interface: The interface as a whole is used for chat dialogue, viewing or sending emoticons, adding trending memes to emoticons, generating trending meme emoticons, sending trending meme emoticons, and synthesizing popular emoticons; certain parts of the interface are used for adding trending memes to emoticons, generating trending meme emoticons, sending trending meme emoticons, and synthesizing popular emoticons. 7. Human-computer interaction method of graphical user interface: In the main view of Design 1, users can drag emoticons to the corresponding hot meme command options to generate emoticons for the corresponding hot meme commands. The human-computer interaction methods of Design 2 and Design 3 are the same as those of Design 1, and users can also slide the command options to view more command content. In the main view of Design 4, users can drag emojis onto the corresponding trending text to generate the corresponding emoji and automatically send it. Design 5 uses the same human-computer interaction method as Design 4, with more trending meme text options displayed at the bottom. In the main view of Design 6, users can click the command option on the left to switch the emoji generated by the corresponding command; they can also click the emoji generated by the corresponding command on the right to send it to a friend. In the main view of Design 7, users can drag emoticons to the corresponding popular emoticons, combine them into an emoticon, and then automatically send the emoticon. In each design, the rounded rectangular blank area in the interface is the content screen, such as: emoticons, pictures, photos, etc.

The invention discloses an interactive audience participation feedback method based on sentiment analysis and behavior prediction. User behavior data and text sentiment information are collected in real time through an audience terminal, behavior analysis and sentiment recognition are executed in parallel on a cloud server, and behavior tags and multi-level sentiment scores are generated; in combination with the historical portrait of the user, personalized interactive feedback content including an expression package, a knowledge point card, a microphone connection invitation or a voting entry is dynamically generated through a weighted scoring mechanism, and the pushing frequency is controlled to be not more than once every three minutes to avoid interference; meanwhile, when the individual continuously carries out negative feedback or the overall negative emotion ratio of the live broadcast room exceeds a threshold value, an instruction is automatically sent to the live broadcast stream pushing end, and real-time content adjustment is achieved. The method effectively solves the problems that traditional live broadcast interaction lags behind, is single in form and lacks emotional response, remarkably improves the audience immersion, participation and platform retention rate, and is suitable for various live broadcast scenes such as education, entertainment and e-commerce.

The present invention provides a device for optimizing emotional responses using a commonsense knowledge graph incorporating emoticons. The device comprises a dictionary graph storage module for storing an emotional lexicon and an emoticon-enhanced commonsense knowledge graph; an emotional context knowledge subgraph generation module for generating an emotional context knowledge subgraph based on the current conversation, the emotional lexicon, and the emoticon-enhanced commonsense knowledge graph; and a response generation module comprising a conditional variational autoencoder for inputting the emotional context knowledge subgraph, the current utterance, and the emotion label into the conditional variational autoencoder to generate an emotional response. In summary, this method can generate emotional responses that are rich in emotional expression and accurate.

The application relates to an Internet community-based emoticon package identification method and device and a storage medium. The method comprises the following steps: acquiring an image in an Internet community, and using a pre-trained image classification model to classify the image to determine whether the image belongs to an emoticon package category; when the image does not belong to the emoticon package category, using an OCR model to acquire a text detection result in the image; determining whether the text detection result contains a keyword in a preset keyword library; when the text detection result contains the keyword, determining whether the text detection result meets a preset filtering condition; when the text detection result meets the preset filtering condition, determining that the image belongs to the emoticon package category, and adding the image to an emoticon package recommendation pool. Through the technical scheme, the accuracy of emoticon package identification is improved.

The present invention relates to the technical field of information processing, and discloses a method, device, electronic device and computer-readable storage medium for generating emoticons. The method for generating emoticons includes: obtaining original materials for generating emoticons; determining the category of the emoticon to be generated and the emoticon generation parameters corresponding to the category of the emoticon; the category of the emoticon includes one or more of the following categories: audio emoticons, static picture emoticons, dynamic picture emoticons, video emoticons; generating an emoticon by using the original materials and the emoticon generation parameters. The present invention realizes the automatic generation of emoticons, reduces the difficulty for users to make emoticons, and also improves the production efficiency and flexibility of emoticons.

The invention provides an expression package generation method and device, electronic equipment, a medium and a program product, and relates to the technical field of data processing, in particular to the fields of video processing, content generation, artificial intelligence and the like. According to the implementation scheme, video data used for generating an emoji package is obtained, wherein the video data comprises content associated with interaction between a first target object and a second target object; based on the video data, time-varying distribution data of interaction strength between the first target object and the second target object is determined, and the distribution data indicates a peak moment when the interaction strength meets a preset standard; performing sequential relationship fusion on the distribution data to determine at least one target moment associated with the peak moment; and extracting a video clip corresponding to the peak moment and the at least one target moment from the video data to generate an expression package.

The invention discloses a virtual human generation method and a related device, and relates to the technical field of virtual humans, emoticons are adopted as bridges between text replies and emotions, emoticons with different intensities are expressed by different emoticons, and the emoticons have different emotion category labels relative to an existing emotion recognition model. Therefore, when the virtual human is generated, the emoticon is utilized to render the expression of the virtual human, the expression expression naturalness and the emotion expression accuracy of the generated virtual human can be guaranteed, the expression generation effect of the virtual human is improved, and then the interaction experience of the user and the interactive virtual human is improved.

The invention discloses an emoji package processing method and device, equipment and a storage medium, and belongs to the technical field of human-computer interaction. The method is executed by a first terminal and comprises the steps that a first object in a virtual environment provided by a chess and card game program is displayed, and the chess and card game program provides the function that at least two objects transmit emoji packages in the virtual environment; displaying at least one expression package sent for the first object; under the condition that at least two expression packages sent for the first object exist, displaying a fusion expression associated with the at least two expression packages; wherein the expression packages are multimedia materials used for transmitting emotion information, and the fusion expression and each expression package in the at least two expression packages have the same elements. By displaying the fused expression, the number of expression packages capable of being transmitted in the virtual environment is increased, and more styles of expression packages can be displayed.

This disclosure relates to a sentiment classification method and apparatus, belonging to the field of natural language processing technology. The method includes: extracting comment text data containing character text and emoticon text; inputting the comment text data into a preset language model to obtain a first feature vector of the character text and a second feature vector of the emoticon text; the preset language model being a language representation model pre-trained using unlabeled first sample comment text data and fine-tuned using labeled second sample comment text data; performing sentiment enhancement processing on the first feature vector according to a preset sentiment dictionary to obtain a third feature vector of the character text; and inputting a concatenated feature vector of the third and second feature vectors into a fully connected layer in the preset language model to obtain the sentiment classification result corresponding to the comment text data. This method reduces reliance on labeled data during sentiment classification and performs sentiment prediction from multiple feature dimensions, improving prediction accuracy.

Embodiments of this disclosure provide a method, system, electronic device, computer-readable medium, and computer program product for displaying emoticons in a conversation. The method includes: displaying a conversation interface, the conversation interface including a conversation display area and an emoticon display area, the emoticon display area displaying at least one emoticon image, the at least one emoticon image including a first emoticon image; causing the conversation display area to enter a point-and-draw state according to a first selection operation on the first emoticon image in the emoticon display area; and displaying the first emoticon image in the first selected area according to a first target operation on the first selected area in the conversation display area. The method, system, electronic device, computer-readable medium, and computer program product for displaying emoticons in a conversation provided by embodiments of this disclosure can achieve efficient user communication based on operations on emoticons.

1. The name of the design product: the main body of the expression input graphical user interface for electronic devices. 2. The use of the design product: an electronic device. 3. The design points of the design product: the part in the graphical user interface, the part outside the dotted line is the claimed part. 4. The picture or photo that best shows the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the overall interface is used for expression input and sending; the claimed part of the interface is used for expression assembly and switching. 7. The human-computer interaction mode of the graphical user interface: in design 1 front view, the user can click the "complete" control to enter the current expression combination into the input box, long press the rounded rectangle expression card control to expand the preview switching window of the corresponding expression library, click the "structure" control to switch the card structure, and click the "random" control to randomly switch the expression combination under the current card structure. The human-computer interaction modes of design 2 and design 3 are the same as those of design 1. In design 4 front view, the user can click the "complete" control to enter the current expression combination into an input box, long press the rounded rectangle expression card control to expand the preview switching window of the appropriate expression library, click the "structure" control to switch the card structure, click the "random" control to randomly switch the expression combination under the current card structure, and click the color disc control at the bottom of the interface to select the color combination to randomly generate the expression combination with the corresponding color. In design 5 front view, when the user clicks the "+ expression combination" control, it enters design 5 interface change state diagram 1; when the user clicks the "complete" control, it enters design 5 interface change state diagram 2. In design 6 front view, when the user clicks the "+ expression combination" control, it enters design 6 interface change state diagram 1; when the user clicks the "structure" control, it randomly switches the expression card structure and enters design 6 interface change state diagram 2. In design 7 front view, when the user clicks the "+ expression combination" control, it enters design 7 interface change state diagram 1; when the user clicks the "random" control, it randomly switches the expression combination and enters design 7 interface change state diagram 2. In design 8 front view, when the user clicks the "+ expression combination" control, it enters design 8 interface change state diagram 1; when the user long presses the leftmost expression card control, it enters design 8 interface change state diagram 2. In the design 9 main view, when the user clicks the "+ emotion combination" control, enter the design 9 interface change state diagram 1; when the user long-presses the middle expression card control, enter the design 9 interface change state diagram 2. In the design 10 main view, when the user clicks the expression combination control at the lower right of the "+ emotion combination" button twice, enter the design 10 interface change state diagram 1; when the user clicks the "send" control, enter the design 10 interface change state diagram 2.

The present invention provides a deep learning-based device for generating emotional responses with emoticons. The device comprises: a dialogue module for generating responses based on a conversational utterance and a specified emotion; an emoticon module for generating a specified emoticon set based on the conversational utterance, the specified emotion, and an emoticon library; a location module for generating sequence annotation results based on the responses and the specified emoticon set; and an integration module for integrating the sequence annotation results, the specified emoticon set, and the responses to generate an emotional response. In short, this method can generate emotionally rich and accurate responses in conversations.

The present application discloses an emoticon package retrieval method, an electronic device, and a computer-readable storage medium. The method includes: obtaining a conversation text, splicing a plurality of relationship supplementary texts for the conversation text, and obtaining a spliced ​​text; wherein each relationship supplementary text corresponds to a preset common sense relationship; based on the spliced ​​text, determining the intention information of the conversation text and the intention fusion text feature corresponding to the conversation text; wherein the intention fusion text feature is fused with the intention information; obtaining a target visual attribute that matches the intention fusion text feature, and obtaining a target emoticon package that matches the intention fusion text feature from an emoticon package collection corresponding to the target visual attribute; wherein the target visual attribute is selected from a plurality of candidate visual attributes, and the candidate visual attribute is determined based on the description text of a plurality of emoticon packages, and each candidate visual attribute corresponds to a respective emoticon package collection. The above scheme can improve the accuracy of emoticon package retrieval.

The invention provides an expression package generation method and device based on a large model, electronic equipment, a readable storage medium and a computer program product, and relates to the field of artificial intelligence, in particular to the field of intelligent generation. According to the implementation scheme, first feature information of a user is determined based on a first conversation between the user and an intelligent agent, and the first feature information at least comprises intention description information about the user; acquiring second feature information of the intelligent agent, wherein the second feature information at least comprises role setting information about the intelligent agent; on the basis of the first feature information and the second feature information, a cue word corresponding to the first dialogue is determined by utilizing a predefined cue word template, and the cue word template at least comprises description information for guiding a large model to map the intention description information and the role setting information into an expression package; and determining an expression package corresponding to the first dialogue by using a large model based on the cue word.

The application discloses an expression package generation method, which comprises the following steps: obtaining a target picture and identifying the target picture; analyzing the identification result of the target picture; selecting a target expression according to the identification result; and generating an expression package based on the target expression. The application further discloses an expression package generation device, equipment and computer readable storage medium. The application combines the target expression with the target picture according to the target expression selected by a user and the target expression selected by the user by obtaining the target picture selected by the user, identifying the target picture, and generating an expression package according to the identification result of the target picture. The application realizes high expression package production efficiency, makes the generated expression package more diversified, and meets the customized needs of users.

The invention discloses a cognitive heuristic multi-modal reasoning method for Chinese harmful expression package detection. The method comprises the following steps of 1, obtaining a Chinese harmful data set; 2, scene-based narrative generation is carried out; 3, multi-granularity visual feature fusion is carried out; step 4, carrying out progressive multi-mode reasoning; and 5, performing model uncertainty weighted multi-loss framework training. According to the invention, by simulating a human cognitive mechanism, a multi-modal recognition framework integrating scene narration, multi-granularity visual perception and progressive reasoning is constructed, and accurate detection of Chinese harmful expression packages is realized.

The application discloses a social text sentiment analysis method and device fusing emoticons, and the method comprises the following steps: preprocessing unannotated emoticon-containing text data and annotated social text data, obtaining pre-training text data, and extracting emoticons in the pre-training text data as pre-training labels; a neural network model is built to pre-train the pre-training text data, and a pre-training model taking emoticons as prediction labels is obtained; the pre-processed annotated social text data is input into the pre-training model, the parameters of the pre-training model are updated through a chain unfreezing method, and a social text sentiment classifier is trained; social text needing sentiment classification is input into the social text sentiment classifier, and a prediction sentiment category is obtained; the application has the advantages that the limitation of emotion information loss caused by social text and emoticon segmentation processing is overcome, and the classification accuracy of social text is improved.

1. Name of the product in this design: Graphical User Interface for Displaying an Expression Clock on an Electronic Device. 2. Purpose of this design: An electronic device. 3. The key design feature of this product is its graphical user interface. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: To display a clock interface with emoticons. 7. Human-computer interaction method of graphical user interface: The main view of Design 1 to Design 5 is the emoticon interface. Clicking on the emoticon pattern in the top layer of the interface will switch to the change state diagram of Design 1 to Design 5 respectively, displaying a clock with the emoticon pattern in the top layer, and the color of the second hand is the same as the color scheme of the emoticon pattern.

1. Name of the product in this design: Graphical User Interface for Emoticon Bullet Screen on Electronic Devices. 2. Application of this design: This design is intended for use in electronic devices. 3. The key design features of this product are the graphical user interface portion of the electronic device for which protection is sought. 4. Images or photos that best illustrate the design points: Interface change state diagram 4. 5. For electronic devices, the rear view, left view, right view, top view, and bottom view are omitted due to conventional design. 6. Purpose of the graphical user interface: This product design is used for sending selfie emojis via bullet comments. 7. Human-computer interaction method of graphical user interface: Clicking the "Face Expression" icon in the lower left corner of the main view will enter the interface change state diagram 1. Clicking the "Shoot" icon in the interface change state diagram 1 will enter the interface change state diagram 2. After confirming that the expression is captured correctly in the interface change state diagram 2, clicking the "Done" button will enter the interface change state diagram 3. Clicking the "Send Expression" button in the interface change state diagram 3 will enter the interface change state diagram 4.

Systems and methods are described herein for inserting emoticons within a media asset based on an audio portion of the media asset. Each audio portion of a media asset is associated with a respective part of speech, and an emotion corresponding to the audio portion for the media asset is determined. A corresponding emoticon is identified based on the determined emotion in the audio portion and presented in the subtitles.

The present application provides a method, device, electronic device, and computer-readable storage medium for interactive processing of information streams. The method includes: displaying at least one piece of information in the information stream and a comment entry corresponding to the at least one piece of information; in response to a triggering operation on the comment entry corresponding to target information, wherein the target information is information to be commented on in the information stream, displaying at least one emoticon material in a comment editing area of ​​the target information, wherein the at least one emoticon material is related to a high-frequency comment word in the information stream, and the comment editing area is used to publish a comment corresponding to the target information based on the at least one emoticon material. Through this application, the efficiency of comment editing can be improved and the expression of comments can be enriched.

The present disclosure provides an expression package generation method, device, electronic equipment, storage medium and product. The method comprises: obtaining event content data of a current event and user portrait data of a user; generating an initial expression package set matched with the user and the current event based on the event content data and the user portrait data; identifying an emotion type and an emotion intensity of the user during watching of a live broadcast of the event; and adjusting display parameters of corresponding expression packages in the initial expression package set according to the emotion type and the emotion intensity, to generate a dynamic expression package adapted to a current emotion state. The expression package can dynamically change with real-time emotions of the user, accurately convey the emotion intensity and real reaction of the user in the current event, and thus meet the demand of the user for more accurate emotion expression.

The invention relates to the field of artificial intelligence processing, in particular to a non-functional interactive personalized random input generation method, which comprises the following steps of S1, acquiring basic data; s2, generating personalized random input; s3, generating content output and interaction feedback receiving; s4, emotion feature fusion extraction: obtaining surface emotion features and scene emotion features, and performing emotion feature fusion; s5, lightweight sentiment classification and multi-modal response scheduling are carried out; s6, outputting emotional response, and synchronously outputting three types of resources including texts, emoticons and voices to the user; s7, user interaction willingness quantitative analysis is carried out; s8, iteration and adjustment of the dynamic threshold value of the interaction intensity; and S9, performing cross-link data multiplexing and full-link reverse iteration. The problems of insufficient content generation adaptability, insufficient emotion response accuracy and real-time performance and low efficiency of an interactive link and an adjustment mechanism in the aspects of an underlying algorithm, a model architecture and a technical mechanism in the traditional technology are solved.