170 results about "Emoji" patented technology

The invention provides a multi-feature fusion rumor detection method, system and device based on knowledge distillation, and mainly solves the problems that an existing model is high in calculation overhead, insufficient in feature fusion and insufficient in emotion utilization. The method comprises the steps of firstly obtaining multi-dimensional data such as social media original texts and comments; extracting deep semantic representation by using a pre-training model, and analyzing comment emotion features in combination with a hybrid neural network; then, features such as semantics, emotions, emoticons and populations are input into a hierarchical gating interactive fusion network (GIFN), and weights are dynamically adjusted to achieve effective fusion of multi-granularity features; in order to reduce complexity, a knowledge distillation framework is designed: a deep GIFN is used as a teacher network to generate a soft label, and a lightweight student network (LSTM) is guided to perform training. According to the trained student model, the parameter quantity is remarkably reduced, meanwhile, good detection performance is kept, the student model can be conveniently deployed in an actual content auditing system or edge equipment, and social content rumors can be efficiently recognized and judged.

The invention belongs to the technical field of dialogue generation, and relates to a digital intelligent carrier pigeon WeChat intelligent dialogue generation method based on deep learning. Dialogue data are obtained, and semantic anomaly detection is carried out through a regular expression and a BERT model in combination with a public corpus; organizing dialogue data in a mode of constructing a tree structure and introducing a three-dimensional timestamp; for emotion information of emoticons, text and visual features of expressions are combined through a hybrid encoder, a dynamic attention mechanism is adopted, weighting and memory length adjustment are carried out according to importance of historical statements, after user portrait features are introduced, user features and dialogue codes are fused, and therefore, the emotion information of the expressions is obtained. In the generation stage, through a Transform-based model and a Beam Search algorithm, a diversity penalty term is introduced in the generation process, and generation parameters are dynamically adjusted according to a user portrait, so that the diversity and security of generated dialogues are ensured, the precision and coherence of a dialogue generation model are improved, and the technical problems of context coherence and personalized generation are effectively solved.

Techniques for transcribing and / or summarizing multimedia collaboration sessions are discussed herein. For example, users can communicate within a teleconferencing meeting associated with a channel. In some examples, a first machine learning model may be configured to receive audio-visual data and user interaction data (e.g., selected emojis, detected gestures, messages or text input by a user, a thread of messages, etc.) and output a teleconferencing meeting summary. In some examples, the teleconferencing meeting summary can include one or more highlights, action items, and / or artificial intelligence (AI) notes generated using a machine learning model(s).

Disclosed are a terminal on which a messenger application for an instant messaging service is installed and an operating method thereof. The terminal is configured to, based on whether a word input by a user to a chat window of the instant messaging service is an event keyword for an advertisement event, display an interfacing object associated with the event keyword, when the user selects the interfacing object, expose at least one piece of advertisement content of a recommended emoticon set and an event banner, in which the recommended emoticon set includes event emoticons associated with the event keyword and the event banner induces an entry to an advertisement event page associated with the event keyword, and based on whether the user participates in the advertisement event, receive a reward corresponding to the advertisement content.

The invention discloses an intelligent communication content adaptation system and method based on user intention recognition. The system integrates and processes texts, voices, emoticons and unstructured behavior data through a multi-modal input analysis module; the deep learning intention recognition engine adopts a triple attention mechanism, current input and weighted historical interaction features are fused, and multi-level intention classification including basic operation, semantic targets and emotion driving is output; the real-time emotion state analysis module fuses acoustics, semantics and physiological indexes to generate a dynamic emotion matrix; the content adaptation decision engine is based on the intention confidence and the emotional state; and the multi-channel output optimization module performs cooperative adjustment on the speech synthesis rhythm, the text abstract and the visual interface according to the speech synthesis rhythm and the text abstract. According to the method, the perception precision of the deep intention and emotion of the user in a complex scene is remarkably improved, the individuation and multi-channel adaptive optimization of the response content are realized, and the communication efficiency and the user experience are effectively improved.

A system including an artificial intelligence (AI) engine and an AI-based method are provided for dynamically predicting and suggesting emojis on a quick access emoji interface. The AI engine detects an input message in an input field on a graphical user interface of a user application. The AI engine processes the input message to identify elements, for example, character elements, image elements, patterns, etc., of the input message. The AI engine analyzes and determines a context and factors, for example, emoji positions, one or more languages, intent, user and global preferences, etc., associated with the input message for each element of the input message. The AI engine dynamically generates predictions of emojis based on the context and one or more factors in real time. The AI engine renders one or more grouped sets of emojis on the emoji interface based on the dynamically generated predictions.

The present technology provides an emoji recommendation service that measures a similarity score between a global emoji embedding space of an online community with a user embedding space generated from the global emoji embedding space and generates a ranking of top emojis based on the measured similarity score. The emoji recommendation service further measures an averaged ranking of top emojis based on the similarity score and term frequency scores in the online community. The emoji recommendation service trains a machine learning algorithm to arrange vectors representing emojis in the global emoji embedding space.

Techniques for transcribing and / or summarizing multimedia collaboration sessions are discussed herein. For example, a user may communicate within a teleconference associated with a channel. In some examples, a first machine learning model may be configured to receive audiovisual data and user interaction data (e.g., selected emoticons, detected gestures, messages or text entered by a user, threads of messages, etc.) and output a teleconference summary. In some examples, the teleconference summary may include one or more highlight points, action items, and / or artificial intelligence (AI) annotations generated using a machine learning model.

The invention discloses a forum lever speech recognition method and device based on deep learning. The method comprises the steps of obtaining comment data and performing preprocessing; calculating a text sentiment score based on sentiment words, negative words, adverbs and exclamation marks in the preprocessed comment data; calculating emoticon emotion scores based on emoticons in the comment data; obtaining a final emotion score based on the text emotion score and the expression emotion score; vectorizing and compressing the preprocessed comment data to obtain text sentence vector representation; performing weighted fusion on the text sentence vector representation and the final sentiment score to obtain sentiment value weighted sentence embedding representation; using the sentiment value weighted sentence embedding representation and the corresponding label to train a sentiment classification model; the trained sentiment classification model is used for identifying whether the speech is a bar-sperm speech or not. According to the method, sentiment words, negative words, adverbs, other words, exclamation marks and emoticons are comprehensively considered, and the recognition problem of the lever speech containing hidden contexts is solved.

The invention discloses an expression robot with variable facial forms. The eyebrow mechanism and the eye mechanism are fixedly connected, the eyebrow mechanism, the eye mechanism and the mouth mechanism are all connected with the deformation mechanism, the eyebrow mechanism, the mouth mechanism and the deformation mechanism are all installed on the head shell mechanism, the neck mechanism is fixedly installed at the bottom end of the mouth mechanism, and switching of multiple states of four freedom degrees of neck stretching, nodding, head shaking and head turning is achieved. The skin color changing mechanism is attached to the head shell mechanism and used for changing the skin color of the robot, the deformation mechanism is mainly driven by a worm and gear structure, and deformation of eyebrows and the mouth of the robot is achieved through the worm and gear structure. According to the machine, self-adaptive face transformation according to human face characteristics is realized, the face shape, pupil color and neck length can be quickly changed according to different application scenes, abundant mouth shapes can be realized, and the requirement of real-time dialogue is met.

A method and a system for performing domain adaptations of social media text by using lexical data transformations are provided. The method includes: receiving a first data set that is usable for training a machine learning (ML) model that is designed to perform natural language processing tasks; training the ML model by using the first data set; receiving a second data set that relates to a social media platform; transforming a subset of the first data set into a third data set that is suitable for the social media platform; and retraining the ML model by using a combination of the first data set, the second data set, and the third data set. The transformations may include injecting emojis, emoticons, user mention indicators, hashtags, retransmission indicators, URLs, and / or inverse lexical normalizations that are often used in social media posts.

1. Name of the product of this design: Recommendation window of a graphical user interface for recommending emoticons for an electronic device. 2. Purpose of the product of this design: an electronic device. 3. The design highlights of this appearance design product are located in the part of the graphical user interface. 4. The picture or photo that best illustrates the design points: Interface change state diagram 1. 5. Purpose of the graphical user interface: The overall purpose of the interface is to recommend emoticons or quotes to users based on information input by users during online chatting; the local purpose is to display the expansion and switching process of the recommendation window. 6. Human-computer interaction method of graphical user interface: The main view is the main interface displayed by the electronic device. When the user clicks the upward arrow in the tray in the main view, the interface jumps to interface change state diagram 1, displaying the emoticon recommendation window; when the user slides left in the recommendation window of interface change state diagram 1, the interface jumps to interface change state diagram 2, displaying the quotation recommendation window; among them, the rounded box area in interface change state diagram 1 is used to display the content screen; the specific interface is shown in the interface usage state reference diagram. 7. Other situations that require explanation: The parts that do not require protection are indicated by dotted lines in the interface.

The technology provides mechanisms to set criteria for when a scheduled send of a communication, such as an email, text message, chat message, etc., should occur. The criteria can be based on the state of a user's message inbox, their communication channels, and / or the status or actions of others to be communicated with. Machine learning can be used to either generate the criteria for when or how to respond, or to generate a recommended response. The system can reformat a communication by changing the tone of a message, or rework the communication for transmission in an alternative format / medium via a different messaging app. This can involve changing from an email message to a chat or audio message, replacing text with emoji or the like, adding visual indicia to the communication, and / or adding audible information to the communication.

The embodiment of the invention provides an expression package generation method and related equipment. The emoticon generation method comprises the steps that in response to uploading of a target picture, use state information and user historical data are acquired, and the use state information comprises a current use scene, a current track and a current emotion; the historical data of the user comprises the use frequency and use scene of each emoji package by the user and emoji package data generated by the user; converting the target picture by using state information and user historical data to generate an undetermined expression package; obtaining user content adjustment information; and according to the user content adjustment information, adjusting the to-be-determined emoji package to obtain a target emoji package. According to the technical scheme provided by the embodiment of the invention, the finally generated expression package is more personalized, efficient adaptability can be kept in various use scenes, and the user experience is improved.

The invention discloses a generation type artificial intelligence safety test method and device based on emoji, and relates to the emoji text generation technology, and the method comprises the steps: constructing a safety keyword library module; constructing an emoji library module; a test case generation module; a test case evaluation module; the method is applied to artificial intelligence. By generating the mixed language test text containing the emoji, a content security case for the safety test of the generative artificial intelligence is constructed, and the content defense capability of the generative artificial intelligence when the emoji text is processed is systematically verified. By adopting the technical scheme of the invention, the anti-emoji avoidance capability of the content security mechanism of the generative intelligent system can be evaluated, and the security defense level of the generative artificial intelligence in a complex text scene can be effectively improved.

A system configured to enhance emotional accessibility of media content depicting one or more characters includes a computing platform having a hardware processor and a memory storing software code. The hardware processor executes the software code to obtain annotation metadata identifying one or more emotions of at least one character, determine, based on the one or more emotions, a mood of the at least one character. The hardware processor further executes the software code to identify, based on the mood of the at least one, one of a plurality of emojis for visually communicating that mood, and generate a visual accompaniment to be displayed in synchronization with displaying the media content to enhance the emotional accessibility of the media content, wherein the visual accompaniment includes the one of the plurality of emojis.

In accordance with some embodiments, a portable electronic device includes: a display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or mor processors. The one or more programs include instructions for: detecting a user-defined gesture on the display while the portable electronic device is in a user-defined-gesture recording mode; creating a representation of the user-defined gesture; associating the representation of the user-defined gesture with an emoji character; and storing the representation of the user-defined gesture and the association of the representation of the user-defined gesture with the emoji character.

The embodiment of the invention discloses a personalized emoticon conversion processing method and system, equipment and a storage medium. According to the technical scheme provided by the embodiment of the invention, the real-time clipboard input information is acquired, and the target emoticon format of the clipboard input information is determined according to the type identifier of the clipboard input information; under the condition that the target emoticon format is not matched with the set general emoticon format, extracting image data in the clipboard input information frame by frame; and sequentially adding the extracted image data to the emoticon construction container corresponding to the general emoticon format, and generating the motion image emoticon corresponding to the general emoticon format based on the emoticon construction container. By adopting the technical means, the universal processing of the personalized emoticons can be realized, so that the personalized emoticons can be applied in a cross-platform, cross-version and cross-application manner, the visual consistency and the functional integrity of the personalized emoticons are kept, and the use experience of a user is improved.

1. Name of this design product: Pack (Emoji Pack). 2. Purpose of this design: To contain items. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. The rear view is shown in the changing state diagram, and is omitted.

The invention discloses an 18-key pinyin input method and device, electronic equipment and a medium, and belongs to the technical field of computer character input. An existing Chinese input method has the defects that the keys are too dense, mistaken touch is prone to occurring, the repeated code rate is high, spelling is inconvenient and the like, and input efficiency is affected. The design that the initial consonant area and the final area are separated is adopted, nine keys are arranged, left-hand and right-hand division input is achieved, conflicts are reduced, and the spelling speed is increased; the initial consonant area key corresponds to two letters, the final area key corresponds to a single letter, and a user-defined key is reserved as a delete key. The character prompt area is provided with double-row display, so that pinyin combination results can be prompted conveniently. Besides the alphabet area, functional keys such as Chinese-English / simple-complex switching, punctuation, emoji, number, space and return are further configured, the function of triggering extension by long pressing is supported, the input position can be moved by long pressing of the space key, and voice input can be performed by long pressing of the return key. By optimizing the number, distribution and interaction mode of the keys, the input efficiency and the operation comfort are both considered, the false touch rate is remarkably reduced, and the Chinese input experience on the mobile equipment is improved.

Provided in the embodiments of the present disclosure are an emoji content processing method and apparatus, and a device, a readable storage medium and a product. The method comprises: in a preset interface, displaying target content associated with second users, and a preset target control; on the basis of preset trigger operations performed by first users on the target control, displaying a preset emoji content generation interface; acquiring emoji content generated in the emoji content generation interface, and displaying the emoji content and a preset sending control in the emoji content generation interface; and in response to a trigger operation on the sending control, sending the emoji content to conversation interfaces associated with the second users. Therefore, the first users can generate emoji content that better meets actual requirements, and can quickly send the emoji content to the conversation interfaces, thereby simplifying the processes of generating and sending the emoji content.

This disclosure relates to a method, apparatus, storage medium, and electronic device for obtaining emoji combinations. The method includes: obtaining multiple candidate emoji combinations from multiple target texts, each candidate emoji combination comprising multiple emojis; for each candidate emoji combination, obtaining one or more adjacent characters from the multiple target texts adjacent to the candidate emoji combination, and obtaining the adjacent character richness of the candidate emoji combination based on the number of the one or more adjacent characters and the adjacent probability of each adjacent character with the candidate emoji combination; obtaining the dependency of the candidate emoji combination based on the probability of the multiple emojis of the candidate emoji combination appearing individually in the multiple target texts and the probability of the candidate emoji combination appearing in the multiple target texts; and determining a target emoji combination based on the adjacent character richness and dependency of each candidate emoji combination.

The invention provides a big language model red team test method and device based on emoticons, and relates to the technical field of artificial intelligence. The emoticon-based big language model red team test method comprises the following steps: acquiring an original red team test problem; identifying sensitive vocabularies from the original red team test problem; using a first emoticon representing sensitive vocabulary semantics to replace sensitive vocabularies in the original red team test question to obtain a first to-be-tested red team question; embedding a second emoticon into the first to-be-tested red team question to obtain a second to-be-tested red team question; wherein the second emoticon is used for de-attacking the theme of the original red team test problem; and utilizing the second to-be-tested red team question to perform red team test on the large language model. According to the method, the red team test can be efficiently and reliably carried out on the large language model.

A text analysis processing for detecting computer-generated text is provided. In some cases, a text-based chat interaction may be initiated and analyzed to determine whether the text-based chat generated by a communicating entity is computer-generated. The text of the chat session may be analyzed to evaluate punctuation, use of emojis, spacing, grammar, words, phrases, and the like to determine a further likelihood of whether the text is computer-generated. A duration of the chat session may be used as a scoring factor. The various probabilities and scores may be combined to provide a composite score.

The invention discloses a multi-modal sentiment analysis and understanding method for social media comments, which comprises the following steps: respectively extracting text sentiment features, expression sentiment features and picture sentiment features from an input social media comment screenshot, and fusing the sentiment features to form multi-modal data sentiment features; the classification model carries out sentiment analysis on multi-modal data sentiment features to obtain sentiment labels of the comments, multi-modal information such as texts, emoticons and pictures in the social media comments is effectively fused, joint training is carried out by utilizing a large model, the relevance among various types of data can be fully mined during sentiment analysis, and the sentiment labels of the comments are obtained. And the accuracy and comprehensiveness of sentiment analysis are improved.

Methods, systems, and storage media for providing a heuristic multilanguage tokenizer in a web browser environment are disclosed. Exemplary implementations can receive a query; generate a query set comprising at least one query token; generate a result set from a searchable phrase, wherein the result set comprises at least one phrase token; generating at least one supplemental set. Determining that any of the sets comprise at least one of: a first character-type, a second character-type, or an emoji. In response to determining the first character-type: determining a word boundary and extracting a diacritic. In response to determining that the query, result set and the supplemental set comprise the second-type or the emoji, adding a space around each second character-type or emoji in the set; and segmenting the set into a plurality of tokens.

A text analysis processing for detecting computer-generated text is provided. In some cases, a text-based chat interaction may be initiated and analyzed to determine whether the text-based chat generated by a communicating entity is computer-generated. The text of the chat session may be analyzed to evaluate punctuation, use of emojis, spacing, grammar, words, phrases, and the like to determine a further likelihood of whether the text is computer-generated. A duration of the chat session may be used as a scoring factor. The various probabilities and scores may be combined to provide a composite score.

A method and system for math education using dice. A first type of dice includes mathematical operations and one or more other emojis to activate a second type of dice when rolled. The second type of dice including bonus points and penalty points for making math calculations using the mathematical operations from the first dice when rolled. The second type of dice also includes one or more second emojis to activate a third dice including one or more third emojis to provide an automatic winner or automatic loser of the math game when rolled. The three different types of dice provide dynamic and different outcomes based on probabilities and possibilities of different dice faces occurring when rolled.

Present disclosure relates to a method and a user equipment (UE) for enhancing multimodal input content. The UE obtains text-blocks associated with multimodal input and determines a plurality of features for each of the text-blocks using a natural language processing (NLP) model and a neural network (NN) model. Further, the UE identifies usage pattern of the plurality of features based on historic data associated with the usage of the plurality of features using NN model. Thereafter, the UE generates personalized text for each of the textblocks based on the plurality of features and usage pattern. The UE inserts personalized emoticons based on context of text-blocks and lingo of each word using user lingo database. Thus, the UE eliminates manual correction of texts and enhances the readability of message / text entered by user.