11 results about "Verbal expression" patented technology

The application discloses a text intention recognition method, an electronic device, a storage medium and a program product; the method comprises the following steps: obtaining a to-be-recognized user question; if there is no corresponding target natural language expression text of the to-be-recognized user question, determining a target structured language text corresponding to the to-be-recognized user question and a first target prompt text, and the first target prompt text is determined according to the vertical field type corresponding to the to-be-recognized user question; inputting the target structured language text and the first target prompt text into a pre-trained intention recognition large model to perform intention recognition, and determining a target natural language expression text corresponding to the to-be-recognized user question, wherein the intention recognition large model is generated by training according to prompt texts corresponding to different vertical field types, thereby solving the problems of low efficiency and low accuracy of structured language intention recognition; the intention recognition large model is used for intention recognition, the target natural language expression text is accurately determined, and the speed, the efficiency and the cost are low.

We provide the system. [Solution] A means of supporting education using machine learning that enables two-way dialogue using a first language and a second language, A means for creating individual learning plans based on the user's native language and target language, A means of providing users with simulated dialogue using a virtual reality environment, A means of collecting and analyzing user learning progress information and providing real-time feedback, A means of displaying subtitles through the user interface to make the dialogue easier to understand, A means of using a robotic device that supports language learning through dialogue in daily life within a home environment, A system that includes means for analyzing a user's question using speech recognition and natural language processing technologies and generating appropriate linguistic expressions.

The application discloses a composition automatic scoring method based on multi-stage learning, and the method comprises the following steps: S1, extracting the shallow language features, emotional features and theme relevance features of the composition; S2, theme relevance feature extraction; S3, construction of a beautiful sentence identification model and extraction of composition style features; S4, training of a base learning machine; and S5, composition vector distributed representation and feature fusion model training and prediction. The application is applied to the field of automatic composition scoring, and a comprehensive and multi-dimensional composition scoring feature is designed for Chinese composition scoring, the detection and discovery of beautiful sentences in the composition are realized, and the beauty degree of language expression in the composition is better considered; meanwhile, the composition automatic scoring based on multi-stage learning is proposed, and multi-angle composition features are effectively combined for composition scoring.

The application provides a man-machine collaborative English long difficult sentence interactive translation and optimization system and method, relates to the English translation technical field, first carries out syntax semantic double-layer initial deconstruction processing to the English long difficult sentence, generates initial deconstruction text containing basic syntax constituent unit splitting result information and the like, then receives the structured adjustment instruction of interactive subjects, cooperatively adjusts the initial deconstruction text, generates intermediate deconstruction text, receives the semantic optimization opinion of interactive subjects again, fuses the related information in the opinion and intermediate deconstruction text, executes translation text semantic adaptation checking and logic coherence iterative optimization, and finally generates a translation text meeting target language expression habits and complete semantics, so that the quality and efficiency of English long difficult sentence translation are effectively improved through man-machine collaboration.

The application discloses a speech processing method and a terminal device, and relates to the technical field of artificial intelligence. The terminal device acquires a speech segment in a speech stream. When a first speech segment in the acquired speech segment has first language expression content and corresponds to a first semantic, if the first semantic matches a target semantic, the terminal device performs speech enhancement processing on the first speech segment. When a second speech segment in the acquired speech segment has second language expression content and corresponds to a second semantic, if the second semantic matches the target semantic, the terminal device performs speech enhancement processing on the second speech segment. The first language expression content and the second language expression content are not completely identical.

The present application relates to the technical field of education and teaching system, and particularly relates to a kind of ideological and political practice task teaching method for virtual and real interactive scene, it obtains the multi-modal behavior data of student in ideological and political practice task virtual interactive scene and carries out feature extraction, obtains the learning state feature of student, then according to learning state feature, obtain the emotional value grade of student, wherein emotional value grade is used to indicate the emotional resonance degree and value identification degree of student in practice learning process, finally according to emotional value grade, obtain the teaching effect score of student.The present application constructs a full range, three-dimensional student state perception system by collecting multi-modal data covering physiological response, behavior trajectory and language expression, realizes the objective quantification of emotional value in the practice of ideological and political education virtual scene, can realize scientific, accurate teaching feedback, solves the problem that current ideological and political practice task teaching method for virtual and real interactive scene cannot automatically evaluate learning effect.

This invention discloses a method and system for generating evaluation reports for in-service education courses based on a multimodal large-scale model, belonging to the interdisciplinary field of artificial intelligence and educational technology. The invention includes: constructing a historical expert evaluation dataset; performing consistency analysis on expert scores; generating consensus scores based on dynamic fusion weights; extracting features from multimodal teaching data such as classroom recordings and courseware documents to obtain five-dimensional features: teaching posture and demeanor, courseware production, language expression, teaching skills, and teaching effectiveness; fine-tuning the large-scale model using a multi-task learning framework, simultaneously learning score prediction and comment generation; finally, inputting the course to be evaluated into the fine-tuned model to obtain predicted scores for each dimension and a course evaluation report. This invention achieves the digital transfer of expert evaluation experience, effectively solves the problem of fusion of multi-expert evaluation opinions, provides support for course decision-making, and improves the efficiency and accuracy of course evaluation.

This invention provides a rapid psychological state assessment system based on emotion color matching, comprising an interactive operation module, a control processing module, a storage module, a display output module, and a power supply module. The interactive operation module collects information on combinations of emotion expressions selected by the user. The control processing module is communicatively connected to the interactive operation module and generates psychological state assessment results based on the emotion expression combinations and the emotion matching database in the storage module. The power supply module provides power to all modules. This invention constructs a non-verbal expression channel through preset combinations of color, texture, and symbol elements. Users only need a single pointing / touch operation to complete emotion feedback, completely eliminating reliance on verbal descriptions, text comprehension, and complex cognitive processing. This provides a first-ever objective assessment path that is accessible and achievable for those with expression difficulties, achieving a substantial breakthrough in the coverage of the assessment population.

The application discloses a wearable brain-computer semantic synchronization device for medical rehabilitation. The device collects language-related electroencephalogram (EEG) through a head-mounted EEG collector, extracts semantic fragments through an intention decoding module, manages context and determines output timing through a semantic synchronization engine, triggers the generation of coherent text / speech through personalized NLG, and realizes real-time alignment of brain intention and language expression. The device is composed of three units: EEG collection, main processing and output. It cooperates with embedded computing or mobile terminals through a head-mounted electrode array. The system has emotion recognition, tone style control, semantic security verification and emergency interruption. It supports long-term wearing, 8-hour endurance and voice / text dual-channel output. It can be connected to rehabilitation training applications, iteratively personalized models through continuous learning, and balance privacy and security, significantly improving the communication efficiency and rehabilitation experience of patients with aphasia, freezing and other diseases.

The present disclosure provides a punctuation judgment method and device, electronic equipment and storage medium, comprising: recognizing the character information, label information, point information and sentence class information of a target sentence, and obtaining a target feature sequence of the target sentence; recombining each character feature in the target feature sequence to obtain label recombination features and point recombination features of the target feature sequence; and performing judgment on the label information and point information of the target sentence according to the label recombination features and the point recombination features, and obtaining a punctuation judgment result of the target sentence. In this way, the present disclosure can guide users to correctly use punctuation marks and improve language expression ability.

The present application relates to the field of artificial intelligence and network information security technology, and particularly relates to a rumor identification method based on multi-source information fusion. The method comprises: obtaining a text to be identified; obtaining content audit original labels returned by a plurality of third-party content audit platforms; mapping heterogeneous labels of different platforms to a unified clue category system to obtain a clue set based on platform content audit; using a rumor clue supplement vocabulary to identify language expression features of the text to be identified to obtain a clue set based on language features; calculating fusion scores of various clues according to the clue set based on platform content audit and the clue set based on language features, and generating a rumor clue representation vector according to a preset threshold; fusing a text representation of the text to be identified with the rumor clue representation vector, and inputting the fusion result into a rumor identification model to obtain a rumor identification result. The present application can unify mapping, supplement and fusion of multi-platform content audit labels and language expression features, reduce the influence of single information source label loss, label heterogeneity and semantic inconsistency on the identification result, and help to improve the accuracy and stability of rumor identification in the public opinion dissemination scenario.