60 results about "Language analysis" patented technology

The invention provides a call center dialogue sentiment analysis method and system fusing voice and text, and relates to the technical field of voice signal processing, and the method comprises the steps: obtaining a voice signal of a call center and a corresponding transliteration text, extracting intonation, speed, sound intensity and pause sentiment features from the voice signal, meanwhile, deep language analysis is carried out on the transliterated text, and semantic emotion features related to context are extracted; and performing cross-modal correlation analysis on the voice emotion features and the semantic emotion features, and generating a time sequence correction coefficient for feature alignment by constructing a corresponding relation analysis framework between feature sequences. According to the method, language emotion information in voice and text is integrated, more accurate and comprehensive recognition of conversation emotion of the call center is realized, customer satisfaction is improved, and reliable emotion analysis basis is provided for efficiently processing customer appeals.

The invention discloses a system and a method for automatically assembling a data analysis process by a large language model based on Faiss, and belongs to the technical field of data analysis and artificial intelligence. The system comprises a client, a server and a data analysis platform. The method comprises: receiving a natural language analysis demand of a user; identifying a user intention as process assembly or suggestion through a large language model; encoding the demand into a query vector, and performing similarity retrieval by using a Faiiss vector library pre-constructed based on the analysis tool description information to obtain a first candidate tool set; inputting the set and original requirements into a large language model for fine arrangement and logic assembly to generate a second candidate tool set; and finally converting into a structured process file which can be directly identified and executed by a data analysis platform. According to the method, the problem that a structured data analysis process cannot be automatically constructed in the prior art is solved, end-to-end intelligent generation from natural language description to an executable analysis scheme is realized, the use threshold is remarkably reduced, and the analysis efficiency is improved.

The invention relates to a method for functional analysis of a source system (1), wherein a syntax tree model (3) is generated from the program code data of the source system (1). In order to propose a method for functional analysis of a source system (1), in particular with extensive program code data, which method makes it possible to better identify interrelated functional units and, with high result quality and at the same time low resource requirements, to improve further processing by means of a large language model, the invention provides that a syntax analysis unit (4) generates a syntax embedding model by decomposing the syntax tree model (3) into individual syntax element embeddings (5), each representing a syntax element, and stores said syntax embedding model in a syntax embedding model memory (6), and that a language analysis unit (8) generates a language embedding model by decomposing the program code data into individual language element embeddings (9), each representing a language element, and stores said language embedding model in a language embedding model memory (10), whereupon, by means of a query unit (12), at least one query embedding (13) is generated from a query (11) representing a functional element of the source system (1) and those syntax element embeddings (5) and language element embeddings (9) which lie within a predefined range of similarity to the query embedding (13) are retrieved from the syntax embedding model memory (6) and the language embedding model memory (10), whereupon the syntax elements represented by the retrieved syntax element embeddings (5) and the language elements represented by the retrieved language element embeddings (9) are transferred as result elements (14) to an output unit (15), which generates therefrom a functional description dataset (16) and outputs the latter.

The application discloses a talk-based multi-modal feature analysis method and electronic equipment, and relates to the technical field of language analysis, and the technical solution points thereof comprise the following steps: collecting multi-modal evaluation data of a talk process of an object to be evaluated, performing feature marking on the multi-modal evaluation data to obtain state feature points; counting the occurrence frequency and feature intensity of the same features in the state feature points to obtain feature correlation parameters; extracting historical language state feature distribution rules in different evaluation scenes from a historical evaluation data set, calculating a language state influence factor between a language state tendency value in the historical evaluation data and the feature correlation parameters according to the historical language state feature distribution rules; and screening a target influence factor from the language state influence factor according to the real-time language state feature distribution characteristics of the current talk scene, so that clear guidance is provided for the subsequent development of intervention strategies.

The invention discloses a platform product optimization and research and development process remodeling method based on AI drive, comprising the following steps: constructing a general MCP service: dynamically generating an OpenAPI standard document through API scanning registration; analyzing the user language and generating a visual chart or a text abstract; analyzing the natural language, and converting the structured data returned by the API into the visual chart or the text abstract for structural integration and feedback; and establishing a non-invasive AI enabling mechanism: intercepting and processing an API calling request, and providing an interaction component through front-end SDK embedding. Through cooperation of the MCP service and the WebAI assistant, low-invasion AI enabling of a traditional platform product is achieved, and the problems that API integration cost is high, task execution is fragmented and the like are solved. And in combination with a plug-in architecture, the platform can quickly expand the AI capability, and the research and development efficiency and the user experience are remarkably improved.

The invention provides a lightweight anaphora ambiguity resolution multi-task learning method, and relates to the technical field of intelligent language processing of a power system, and the method comprises the steps: S1, collecting power production command related documents to construct a lightweight power semantic knowledge base; s2, on the basis of the lightweight electric power semantic knowledge base, constructing an ultra-lightweight semantic analysis model through double-layer knowledge distillation; s3, performing lightweight deployment on the ultra-lightweight semantic analysis model based on an INT8 quantification technology to obtain a quantification model capable of running on edge equipment; s4, inputting the electric power semantic analysis task into a quantitative model obtained by lightweight deployment by adopting an end-side collaborative reasoning strategy, performing complexity evaluation and intelligent shunting processing, and outputting a semantic analysis result with high confidence; according to the method, high-precision semantic understanding under the condition of extremely low computing resources can be realized, and a practical and reliable intelligent language analysis capability is provided for a power production command system.

The invention discloses a fault processing method, a communication device and a system. The method comprises the following steps: receiving a first request; the first request is related to the fault information; performing language analysis on the first request to obtain a language analysis result; first information is sent, the first information is determined based on the language analysis result, and the first information is used for indicating a request result of the first request. The method can process the request through the first node, does not depend on manpower, and can improve the time consumption of fault processing.

The invention provides a credit report generation system and method based on a language analysis large model, and relates to the field of generative artificial intelligence. The system comprises an interaction layer, an intelligent agent layer, a basic platform layer and a data layer. The data layer is configured to access and store multi-source heterogeneous data of bank users; the interaction layer is configured to receive and output a report template and user information input by a user to the basic platform layer; the basic platform layer is configured to call a workflow corresponding to the report template, call at least one kind of heterogeneous data required by report generation from the data layer, and perform structured processing on user information and the called heterogeneous data to obtain a structured data set; and the agent layer is configured to construct prompt information interacting with a preset language analysis large model based on the workflow and the structured data set, call the language analysis large model based on the prompt information to generate a credit report, and feed back the credit report to the interaction layer to be displayed to a user.

The invention discloses a chat record crime element automatic labeling method based on natural language processing, and relates to the technical field of electronic data intelligent analysis, and the method comprises the following specific steps: sequentially carrying out data preprocessing to analyze multi-platform data and uniformly encode, carrying out semantic analysis to identify crime intentions and entities, and carrying out entity association reasoning on crime elements; and marking elements by using a structured label, and finally carrying out risk scoring and generating a judicial analysis report so as to form a complete crime element analysis process. According to the method, multi-language processing, dynamic weight and hybrid reasoning technologies are integrated, multi-platform data are compatible, the multi-language analysis problem is solved, the criminal entity recognition precision is improved, and the labeling efficiency and accuracy are greatly improved; meanwhile, a full-link judicial system is constructed, crime elements are standardized, electronic evidence export is supported, case mastering is assisted through risk scoring and multi-dimensional reports, a rule base is dynamically updated to adapt to new crimes, the working intensity of judicial personnel is reduced, and reliable support is provided for network crime attack.

The invention discloses a legal document fall positioning and quality inspection method and device based on semantic understanding, and relates to the technical field of legal review, and the method comprises the steps: analyzing electronic document data, extracting text content, associating the text content with corresponding coordinate metadata, and generating multi-modal document data; performing deep semantic and structural analysis on the multi-modal document data, extracting a text sequence, executing natural language analysis and semantic analysis, obtaining a phrase role labeling result, judging a termination position, and obtaining a semantic boundary; based on the semantic boundary and the coordinate metadata, performing retrieval positioning on the multi-modal document data, extracting coordinate text data and page evidence image segments, obtaining a structured entity and segmented signature blocks through entity recognition and signature detection, and constructing a signature element map; according to the method, automatic verification and accurate fund positioning of the document are realized, the processing efficiency is improved, manual intervention is reduced, and the method is widely applicable to automatic examination and compliance inspection of the electronic document.

This application belongs to the field of financial technology and is applied to the training of intelligent customer service question-answering models in the insurance industry. It relates to a GraphQL-based Chinese question-answering model training method and related equipment. The method includes generating GraphQL query statements corresponding to target Chinese question data according to GraphQL specifications; obtaining answer data corresponding to the target Chinese question data through a language analysis model; constructing a first text pair set and a second text pair set, inputting them into a T5 question-answering model pre-trained in an end-to-end mode for T5 question-answering model training, and obtaining a trained T5 question-answering model; obtaining new Chinese question data and inputting it into the trained T5 question-answering model to obtain the model output as answer data. By introducing a dual-tower model structure into the end-to-end T5 question-answering model and constructing query statements according to GraphQL specifications, an end-to-end Chinese graph question-answering model with effective intermediate representations is trained, and the output of the answer data is subject to good quality control.

This application relates to the field of requirements analysis technology, specifically providing an AI-based natural language requirements analysis method and system. The method includes the following steps: acquiring natural language requirements text, then using AI-based feature extraction technology to extract features from the natural language requirements text to obtain text domain features, user style features, and task features; determining the combination of language analysis modules and the parameters corresponding to each language analysis module in the combination based on the text domain features, user style features, and task features; determining the execution order of each language analysis module in the combination based on the text domain features and task features, then constructing a requirements analysis process based on the execution order and the combination of language analysis modules; and using the requirements analysis process to perform requirements analysis on the natural language requirements text to obtain requirements information. This method enables the analysis process to adapt to users' personalized expressions and accurately analyze different analysis tasks.

The invention discloses an unmanned aerial vehicle visual angle three-dimensional visual positioning method, which comprises the following steps: extracting candidate objects and landmarks from a three-dimensional scene, extracting object features by using an object encoder, and extracting landmark features by using a landmark encoder; constructing a language analysis strategy based on prompt learning, and analyzing the overall natural language description into a plurality of partial language descriptions; constructing an object feature enhancement module based on landmark reference, describing and mining neighbor features between an object and a landmark by using a part of natural languages to enhance feature representation of objects near the landmark, and guiding a positioning network to pay attention to the objects near the landmark; an object fine positioning module based on relation perception is designed to make full use of relation information between objects, and unmanned aerial vehicle visual angle three-dimensional visual positioning is achieved.

A language processing computer is provided that can improve the accuracy of language analysis and the accuracy of semantic analysis, which are the prerequisites for learning by artificial intelligence. [Solution] The language processing computer 1 comprises a syntactic analysis unit 110 that performs syntactic analysis of an input document and divides the document into word-based elements; a mapping unit 120 that maps each of the divided words to a semantic structure; an evaluation unit 130 that evaluates the semantic match or similarity between the words divided into word-based elements; a memory unit 300 that associates each word, the evaluated score, and the document and stores them as a semantic unit dictionary; an extraction unit 210 that extracts character strings from a specified document in units of phrases, propositions, or logic based on the semantic unit dictionary; and a processing unit 220 that processes the analysis or translation of the specified document based on the extracted character strings.

The invention relates to the technical field of multi-language processing, and discloses an intelligence mining platform for multi-language data processing, which comprises a multi-source heterogeneous data access module for converting multi-field original data into intermediate format data; the multi-language adaptive analysis module performs language detection, semantic alignment and language analysis on text data, audio and video data and structured data in the intermediate format data to generate analysis results containing semantic vectors; a multi-format data processing module extracts key information with a cross-language semantic identifier from an analysis result; the heterogeneous data fusion module associates and fuses the key information, and constructs a knowledge graph and an event chain to form unified knowledge representation; the knowledge extraction and generation module extracts intelligence elements from the knowledge spectrogram or the event chain. Through multi-module cooperative processing, unified access, analysis, key information extraction, fusion and intelligence generation of multi-language and multi-format data are realized, and structured and high-value intelligence support is provided for related fields.

The application belongs to the technical field of intelligent sports auxiliary learning. A body movement learning clue labeling method and system based on cross-modal mapping are proposed. Language analysis is performed on the voice explanation in the action teaching video to obtain sentence-by-sentence text and corresponding time markers. The sentence-by-sentence text is analyzed to extract entities in the sentence-by-sentence text and the corresponding roles of each entity. The motion characteristics of the action demonstration subject are extracted from the action teaching video. The recognized entities are mapped to graphics to generate visual clues. According to the visual clues, language analysis results and motion characteristics, the visual clues are laid out to the corresponding time and space positions to obtain the final body movement learning clue labeling result. By constructing an optimized graphic clue, the action points can be more intuitively and vividly presented, helping learners clearly understand the action essentials through intuitive visual prompts, and improving the learning effect.

To provide a system for supporting the intellectual training and growth of a child while reducing the labor of a parent.SOLUTION: The voice recognition system includes a means for acquiring voice uttered by a user, a voice recognition means for converting the acquired voice into text data, and a communication means for transmitting the converted text data. A system comprising: language analysis means for extracting a user's intention and emotional state; response generation means for generating an appropriate response based on the extracted intention and emotional state; communication means for receiving the generated response as text data; speech synthesis means for converting the received response text into voice data; and voice changer means for applying character voices to the converted voice data.SELECTED DRAWING: Figure 1

An object of the system according to the embodiment is to correct a user's text in real time and prevent misunderstanding and trouble.SOLUTION: A system includes a language analysis unit, a correction unit, an application providing unit, and an SNS function addition unit. The language analysis unit analyzes the text of the user. The proofreading unit proofreads the text analyzed by the language analysis unit in real time. The application providing unit provides the text proofread by the proofreading unit to the user. The SNS function adding unit provides the text proofread by the proofreading unit to the SNS.SELECTED DRAWING: Figure 1

The invention relates to the technical field of natural language processing, and discloses an AI role-oriented multi-dimensional consistency test system, which comprises the following steps of: extracting core role characteristics of an AI role according to an application scene of the AI role so as to construct a dynamic role map of the AI role; quantifying the dimension weight of the role dimension corresponding to the dynamic role map; a basic test case library of the role dimension is established, and the basic test case library comprises a standardized problem set and a scene script, so that a dynamic derivative case of the role dimension is generated; a cross-dimension conflict use case of a dynamic derivative use case is introduced, a multi-layer test engine of role dimensions is established, and the multi-layer test engine comprises a surface language analysis layer, a logical reasoning verification layer and a value alignment evaluation layer; and calculating cognitive load indexes of the AI roles to establish a multi-dimensional scoring matrix of the AI roles, and calculating global consistency indexes of the AI roles through the multi-dimensional scoring matrix. According to the invention, the accuracy of the AI role multi-dimensional consistency test can be improved.

Provide a system. 【Solution means】 Means for collecting the behavioral information of human resources in the sales operation, Means for centrally managing the collected information and storing it in an immediately accessible storage medium, Means for interpreting the response content and creating an evaluation using language data processing, Means for immediately providing a reverse feed based on the interpretation result, Means for automatically optimizing the work schedule considering the working hours and workload, Means for proposing an education plan based on individual behavioral results, Means for immediately displaying customer information and product information when human resources conduct sales activities using a visual assistance device, A system including means for analyzing the dialogue with customers through voice recognition and language analysis and providing information based on the results.

An object of a system according to an embodiment is to perform mutual translation between speech and sign language in real time.SOLUTION: A system according to an embodiment includes a voice input unit, a sign language translation unit, a sign language expression unit, a sign language analysis unit, a character conversion unit, and a voice conversion unit. The voice input unit receives a voice of a user. The sign language translation unit translates the speech received by the speech input unit into sign language. The sign language expression unit visually expresses the sign language translated by the sign language translation unit. The sign language analysis part analyzes sign language photographed by a camera. The character conversion unit converts the sign language analyzed by the sign language analysis unit into characters. The speech conversion unit converts the sign language analyzed by the sign language analysis unit into speech.SELECTED DRAWING: Figure 1

The present invention relates to an English learning support system based on precise voice recognition. The English learning support system comprises: a language analysis terminal for receiving English voice data spoken by a user, analyzing the pronunciation accuracy and the accuracy of sentences and transmitting same online, and receiving and outputting, with respect to the input English voice data, learning and training data required for English learning; a main server for storing the English voice data of the user received from the language analysis terminal, analyzing the level of pronunciation and the level of sentences of the user to evaluate the level of pronunciation and a sentence composition ability score of the user, and providing training data for English learning on the basis of same; a database management server for storing learning data including English pronunciation, the level of sentences, and learning progress information about the user; and a document-type server for storing the learning and training data required for learning and training as content or learning data. The main server is configured to: calculate the problem difficulty level and a problem rate on the basis of the ability score obtained by evaluating the pronunciation accuracy and sentence accuracy of the user input by means of the language analysis terminal and then provide a learning and training program; update the ability score of the user in real time; and adjust the problem difficulty level and the problem rate by reflecting the updated ability score and then provide the learning and training data again.

The invention relates to a software source code analysis method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: performing language analysis processing on a source code of software to be analyzed to obtain an intermediate language of the source code; based on the intermediate language, performing basic analysis processing on the source code to obtain a basic analysis result of the source code; performing dependency analysis processing on the basic analysis result through a pre-constructed code analysis model to obtain a dependency analysis result of the source code; based on the dependency analysis result, performing multi-dimensional deep analysis processing on the source code to obtain a deep analysis result of the source code; and obtaining a code analysis result of the source code according to the basic analysis result, the dependency analysis result and the deep analysis result. By adopting the method, the analysis precision of the software source code can be improved.

We provide the system. [Solution] A means for storing information related to product attributes in an integrated manner, A language analysis tool that interprets user questions in natural language, A notification mechanism to inform the appropriate department based on the analysis results, A response-forming means that provides the interpreted information to the user in voice or text, A conversion means that enables the output of information using numerical representation software according to the user's request, A means of facilitating communication that dynamically responds to questions from customers in the store and automatically contacts sales staff, A system that includes this.

An automatic sentence mapping system analyzes one or more input sentences to identify one or more associated education language standards such as Common Core English Language Arts (CCELA). One of the main components of the automatic sentence mapping system is mapping functions library. The mapping functions library includes information regarding various educational language standards. For each educational language standard, a set of functions within the standards are defined for validating the input sentences against a specific standard. Most functions defined within an educational language standard are designed for grammatical checks within a sentence against the associated educational language standard while some functions are designed for complex linguistic analysis that leverage artificial intelligence, such as large language models, for performing checks on the sentence for the desired associate language standard.

The system according to the embodiment aims to facilitate communication with foreign tourists and provide high-quality tourist information. [Solution] A system according to an embodiment includes a language recognition unit, a question analysis unit, an answer provision unit, a plan proposal unit, and an information collection unit. The language recognition unit recognizes the language of the tourist. The question analysis unit analyzes the question based on the language recognized by the language recognition unit. The answer provision unit provides an answer based on the question analyzed by the question analysis unit. The plan proposal unit proposes a sightseeing plan tailored to the tourist's interests and concerns based on the information analyzed by the question analysis unit. The information collection unit collects information on tourist destinations.

We provide the system. [Solution] A means of receiving electronic messages via a computer network, A means for linguistically analyzing the content of a received electronic message, A means for detecting a specific tone of voice contained in a message based on the results of language analysis, A conversion means for correcting specific expressions based on the detected tone of voice, A means of sending the revised electronic message, A system that includes this.

The invention relates to the technical field of computer data processing, in particular to a language analysis method and system based on a fast thinking-evaluation-slow thinking aspect level sentiment analysis framework. The framework comprises a large reasoning model and a large evaluation model, the large reasoning model is responsible for aspect emotion reasoning, and the large evaluation model is responsible for evaluating reasoning correctness to prevent cognitive deviation. The large reasoning model firstly generates a preliminary emotion and reasoning process in a target aspect in a fast thinking stage. Then, the large evaluation model evaluates the reasoning. If inference is considered to be correct, the emotion result is adopted. Otherwise, the reasoning large model enters a slow thinking stage, the reasoning evaluation reasonability is reflected, the original reasoning is selectively corrected or reserved, and dynamic correction is achieved. The method can effectively enhance the understanding ability of a large model for complex text sentiment, and significantly improve the accuracy of sentiment judgment.

A system described herein may receive audio associated with a voice call; determine an amount of speech in the audio associated with the voice call; determine, based on the amount of speech, an expected length of a transcript, associated with a particular language, of the voice call; generate or receive the transcript, associated with the particular language, of the voice call; identify a length of the transcript, associated with the particular language, of the voice call; compare the length of the transcript to the expected length of the transcript; determine, based on comparing the length of the transcript to the expected length of the transcript, whether the voice call is associated with the particular language; and output an indication of whether the voice call is associated with the particular language.