565 results about "Natural language understanding" patented technology

Application authoring techniques, and information browsing mechanisms associated therewith, which employ programming in association with mixed-initiative multi-modal interactions and natural language understanding for use in dialog systems. Also, a conversational browsing architecture is provided for use with these and other authoring techniques.

Application authoring techniques, and information browsing mechanisms associated therewith, which employ programming in association with mixed-initiative multi-modal interactions and natural language understanding for use in dialog systems. Also, a conversational browsing architecture is provided for use with these and other authoring techniques.

Methods and systems for dynamic natural language understanding. A hierarchical structure of semantic categories is exploited to assist in the natural language understanding. Optionally, the natural language to be understood includes a request.

A Natural Language Understanding system is provided for indexing of free text documents. The system according to the invention utilizes typographical and functional segmentation of text to identify those portions of free text that carry meaning. The system then uses words and multi-word terms and phrases identified in the free to text to identify concepts in the free text. The system uses a lexicon of terms linked to a formal ontology that is independent of a specific language to extract concepts from the free text based on the words and multi-word terms in the free text. The formal ontology contains both language independent domain knowledge concepts and language dependent linguistic concepts that govern the relationships between concepts and contain the rules about how language works. The system according to the current invention may preferably be used to index medical documents and assign codes from independent coding systems, such as, SNOMED, ICD-9 and ICD-10. The system according to the current invention may also preferably make use of syntactic parsing to improve the efficiency of the method.

A natural language understanding system is described which provides for the generation of concept codes from free-text medical data. A probabilistic model of lexical semantics, in the preferred embodiment of the invention implemented by means of a Bayesian network, is used to determine the most probable concept or meaning associated with a sentence or phrase. The inventive method and system includes the steps of checking for synonyms, checking spelling, performing syntactic parsing, transforming text to its "deep" or semantic form, and performing a semantic analysis based on a probabilistic model of lexical semantics. In the preferred embodiment of the invention, spell checking and transformational processing as well as semantic analysis make use of semantic probabilistic determinations.

In an automatic speech recognition post processing system, speech recognition results are received from an automatic speech recognition service. The speech recognition results may include transcribed speech, an intent classification and / or extracted fields of intent parameters. The speech recognition results are post processed for use in a specified context. All or a portion of the speech recognition results are compared to keywords that are sensitive to the specified context. The post processed speech recognition results are provided to an appropriate application which is operable to utilize the context sensitive product of post processing.

A method of integrating conversational speech into a multimodal, Web-based processing model can include speech recognizing a user spoken utterance directed to a voice-enabled field of a multimodal markup language document presented within a browser. A statistical grammar can be used to determine a recognition result. The method further can include providing the recognition result to the browser, receiving, within a natural language understanding (NLU) system, the recognition result from the browser, and semantically processing the recognition result to determine a meaning. Accordingly, a next programmatic action to be performed can be selected according to the meaning.

A navigation method of man-machine interaction includes receiving audio input data of user by audio input unit, processing audio input data of user by automatic audio identification process and converting it to be relevant command, searching databank according to command execution result of GPS and generating man-machine interactive information with user then outputting said man-machine interactive information by voice synthetic unit.

The invention provides a question and answer method based on a knowledge map. The question and answer method based on a knowledge map provided in the invention is realized by subject entity matching,relationship matching and answer determination. The subject entity matching mainly comprises naming entity identification and entity linking. The naming entity identification is aimed at identifying naming entities such as names of people, names of places, and names of organizations in natural language questions q. The entity linking corresponds the identified naming entity to a certain entity inthe knowledge base, that is, finding out an entity s in triples; Relationship matching is to understand the semantics expressed by question q through natural language understanding technology, and match the relationship p in the triples (s, p, o) in the search space in order to determine the semantics of the question and its corresponding relationship with the knowledge base. The candidate subjectentity is obtained through entity identification and entity linking, and the relationship matching can obtain the candidate relationship, thereby obtaining several candidate triples; the answer determination is to rank the candidate triples according to entity recognition score, relationship match score, etc. to determine the final answer.

A method and system for use in a natural language understanding system for including grammars within a statistical parser. The method involves a series of steps. The invention receives a text input. The invention applies a first context free grammar to the text input to determine substrings and corresponding parse trees, wherein the substrings and corresponding parse trees further correspond to the first context free grammar. Additionally, the invention can examine each possible substring using an inventory of queries corresponding to the CFG.

The invention disclosed herein concerns a system (100) and method (600) for building a language model representation of an NLU application. The method 500 can include categorizing an NLU application domain (602), classifying a corpus in view of the categorization (604), and training at least one language model in view of the classification (606). The categorization produces a hierarchical tree of categories, sub-categories and end targets across one or more features for interpreting one or more natural language input requests. During development of an NLU application, a developer assigns sentences of the NLU application to categories, sub-categories or end targets across one or more features for associating each sentence with desire interpretations. A language model builder (140) iteratively builds multiple language models for this sentence data, and iteratively evaluating them against a test corpus, partitioning the data based on the categorization and rebuilding models, so as to produce an optimal configuration of language models to interpret and respond to language input requests for the NLU application.

A system, method, and computer program product for natural language understanding, including forming pairs of words and / or phrases in independent phrases in a sentence, wherein each word and / or phrase is paired with every other word and / or phrase; determining meanings for the words and / or phrases; comparing the meanings of each word and / or phrase with each meaning of the other word and / or phrase in the pair; selecting the pairs with the best relationships; combining highly-related pairs with other highly-related pairs to form longer groups of words; exchanging word meanings for the longer groups with word meanings having a weaker relationship to determine if the exchanged word meanings provide an overall stronger relationship; and forming longer and longer groups until the sentence is understood.

A Natural Language Understanding system is provided for indexing of free text documents. The system according to the invention utilizes typographical and functional segmentation of text to identify those portions of free text that carry meaning. The system then uses words and multi-word terms and phrases identified in the free to text to identify concepts in the free text. The system uses a lexicon of terms linked to a formal ontology that is independent of a specific language to extract concepts from the free text based on the words and multi-word terms in the free text. The formal ontology contains both language independent domain knowledge concepts and language dependent linguistic concepts that govern the relationships between concepts and contain the rules about how language works. The system according to the current invention may preferably be used to index medical documents and assign codes from independent coding systems, such as, SNOMED, ICD-9 and ICD-10. The system according to the current invention may also preferably make use of syntactic parsing to improve the efficiency of the method.

A system and method for providing a voice assistant including receiving, at a first device, a first audio input from a user requesting a first action; performing automatic speech recognition on the first audio input; obtaining a context of user; performing natural language understanding based on the speech recognition of the first audio input; and taking the first action based on the context of the user and the natural language understanding.

A portable music device may operate in response to user speech. In situations in which the music device is operating primarily from battery power, a push-to-talk (PTT) button may be used to indicate when the user is directing speech to the device. When the music device is receiving external power, the music device may continuously monitor a microphone signal to detect a user utterance of a wakeword, which may be used to indicate that subsequent speech is directed to the device. When operating from battery power, the device may send audio to a network-based support service for speech recognition and natural language understanding. When operating from external power, the speech recognition and / or natural language understanding may be performed by the music device itself.

A method and system, which may be implemented by employing a program storage device readable by machine, and tangibly embodying a program of instructions executable by the machine to perform method steps for ensuring robustness of a natural language understanding (NLU) system, includes tagging recognized words of a command input to the NLU system to associate the command with a context, and translating the command to at least one formal command based on the tagged words. A top ranked formal command is determined based on scoring of the tagged recognized words and scoring translations of the at least one formal command. Whether the top ranked formal command is accepted is determined by comparing a feature vector of the top ranked formal command to representations of feature vectors stored in an accept model. The top ranked formal command is executed if accepted and incorrect commands are prevented from execution to provide a robust NLU system.

Enabling natural language understanding using an X+V page of a multimodal application implemented with a statistical language model (‘SLM’) grammar of the multimodal application in an automatic speech recognition (‘ASR’) engine, with the multimodal application operating in a multimodal browser on a multimodal device supporting multiple modes of interaction including a voice mode and one or more non-voice modes, the multimodal application operatively coupled to the ASR engine through a VoiceXML interpreter, including: receiving, in the ASR engine from the multimodal application, a voice utterance; generating, by the ASR engine according to the SLM grammar, at least one recognition result for the voice utterance; determining, by an action classifier for the VoiceXML interpreter, an action identifier in dependence upon the recognition result, the action identifier specifying an action to be performed by the multimodal application; and interpreting, by the VoiceXML interpreter, the multimodal application in dependence upon the action identifier.

A system, method, and computer program product for domain-independent natural language understanding, including at least one of forming pairs of words and / or phrases in a sentence, wherein each word and / or phrase is paired with every other word and / or phrase; determining meanings for the words and / or phrases; assigning numeric codes that uniquely identify semantic concepts to those word and / or phrase meanings; comparing the numeric code of each word and / or phrase with each numeric code of the other word and / or phrase in the pair; selecting the pairs with the best relationships; combining highly-related pairs with other highly-related pairs to form longer groups of words; exchanging numeric codes for the longer groups with numeric codes having a weaker relationship to determine if the exchanged numeric codes provide an overall stronger relationship; and forming longer and longer groups until the sentence is understood.

The invention discloses a full text retrieval system based on natural language understanding, comprising: a database server, an information receiving judging module, a natural language processing module, a retrieving module, an indexing module, an index database and a result set processing module. The system of the invention provides two resolution strategies, that is, word classification static with semantic analysis associated with automatic segmentation and expanding inquired word static according to Hownet rule for low intelligence situation of current search engine. The deployed system converts information retrieval from current key word-based layer to knowledge (or concept)-based layer; the invention is capable of using techniques such as word classification, synonym, concept search, phrase identification, etc. with understanding and processing ability to knowledge. The search engine is provided with intelligence and humanization of information service. The user is allowed using natural language for information retrieval. The invention is capable of adding user selection behavior in interactive operation mode, so as to provide more convenient, more precise search service.

Disclosed are systems, methods, circuits and associated computer executable code for deep learning based natural language understanding, wherein training of one or more neural networks, includes: producing character strings inputs ‘noise’ on a per-character basis, and introducing the produced ‘noise’ into machine training character strings inputs fed to a ‘word tokenization and spelling correction language-model’, to generate spell corrected word sets outputs; feeding machine training word sets inputs, including one or more ‘right’ examples of correctly semantically-tagged word sets, to a ‘word semantics derivation model’, to generate semantically tagged sentences outputs. Upon models reaching a training ‘steady state’, the ‘word tokenization and spelling correction language-model’ is fed with input character strings representing ‘real’ linguistic user inputs, generating word sets outputs that are fed as inputs to the word semantics derivation model for generating semantically tagged sentences outputs.

The invention discloses a man-machine conversation system applied to an advanced service robot. The man-machine conversation system is characterized in that a voice recognition module, a natural language understanding module, a background service processing module, a natural language generating module and a voice generating module are included and are respectively and independently connected with a conversation management module and used for bidirectional data transmission. The man-machine conversation system has the advantages that the advanced service robot can directly communicate with the human language, the influence caused by a traditional communication way on communication efficiency is avoided, the convenience of man-machine communication is greatly improved, and the aim that the service robot directly listens to human voice instructions is achieved.

The invention discloses natural language understanding method, comprising the steps that: a natural language is matched with a conceptual language symbol after receiving the natural language input by the customer, and then a conception is associated with the conceptual language symbol; a conception which is most suitable to the current language content is selected by being compared with the preset conception dictionary, and then whether the conception is ambiguous is judged; and if the answer is YES, the conception is obtained by a language data base, entering the next step; and if the answer is NO, the conception is obtained based on the principle of language content matched, entering to the next step; a core conception and a sub conception are obtained by a conception reorganization, wherein, the core language meaning of the core conception is defined by an operation of the computer while the sub language meaning of the sub conception is defined by the operation content of the computer; and the complete language meaning is obtained by combining the core language meaning with the sub language meaning. The invention also provides a human-computer interaction intelligent system based on the method provided by the invention. The invention recognizes the natural sound input by the customer more accurately, thereby providing the customer with more intelligent and perfect services.

The invention discloses a natural language understanding method and a travel question-answering system based on the same. The natural language understanding method is characterized in that questions are matched with questions in a syntax database, answers are extracted from a knowledge database according to functions and parameters corresponding to the questions, the syntax database contains most questions in the domain, questions out of the domain are provided through non-domain knowledge databases, the acquired answers are allowed to conform to the context when a user asks the questions by reading the related data of historical questions in a cache, and the accurate answers and related answers are provided. When the method is used for the travel question-answering system, more than 99% pf questions in the travel domain can be covered, the answers out of the travel domain can be extracted, the related answers can be provided, and tests show that accuracy can reach more than 95%.

The invention relates to a task classification system (900) that interacts with a user. The task classification system (900) may include a recognizer (920) that may recognize symbols in the user's input communication, and a natural language understanding unit (900) that may determine whether the user's input communication can be understood. If the user's input communication can be understood, the natural language understanding unit (930) may generate understanding data. The system may also include a communicative goal generator that may generate communicative goals based on the symbols recognized by the recognizer (920) and understanding data from the natural language understanding unit (930). The generated communicative goals may be related to information needed to be obtained from the user. The system may further include a sentence planning unit (120) that may automatically plan one or more sentences based on the communicative goals generated by the communicative goal generator with at least one of the sentences plans being output to the user.

Method and apparatus for providing a personalized self-support service to a user of an online application coupled with an online community forum. Embodiments include obtaining a plurality of questions from the online community forum and obtaining historical user data. Embodiments further include identifying one or more part-of-speech words in the plurality of questions and generating a high-dimensional vector for each question of the plurality of questions based on a frequency of the one or more part-of-speech words. Embodiments further include identifying one or more user features of the plurality of users based on the historical user data and establishing, based on the historical user data, one or more statistical correlations between user features and part-of-speech words. Embodiments further include training a predictive model based on the one or more statistical correlations. Embodiments further include using the predictive model to predict to provide one or more relevant questions to the user.

A dialog with a conversational virtual assistant includes a sequence of user queries and systems responses. Queries are received and interpreted by a natural language understanding system. Dialog context information gathered from user queries and system responses is stored in a layered context data structure. Incomplete queries, which do not have sufficient information to result in an actionable interpretation, become actionable with use of context data. The system recognizes the need to access context data, and retrieves from context layers information required to transform the query into an executable one. The system may then act on the query and provide an appropriate response to the user. Context data buffers forget information, perhaps selectively, with the passage of time, and after a sufficient number and type of intervening queries.

A method of probabilistic error-tolerant natural language understanding. The process of language understanding is divided into a concept parse and a concept sequence comparison steps. The concept parse uses a parse driven by a concept grammar to construct a concept parse forest set by parsing results of speech recognition. The concept sequence comparison uses an error-tolerant interpreter to compare the hypothetical concept sequences included by the concept parse forest set and the exemplary concept sequences included in the database of the system. A most possible concept sequence is found and converted into a semantic framed that expresses the intention of the user. The whole process is led by a probability oriented scoring function. When error occurs in the speech recognition and a correct concept sequence cannot be formed, the position of the error is determined and the error is recovered according to the scoring function to reduce the negative effect.

A natural language understanding system is described to provide generation of concept codes from free-text medical data. A probabilistic model of lexical semantics, is implemented by means of a Bayesian network, and is used to determine the most probable concept or meaning associated with a sentence or phrase. The inventive method and system includes the steps of checking for synonyms, checking spelling, performing syntactic parsing, transforming text to its "deep" or semantic form, and performing a semantic analysis based on a probabilistic model of lexical semantics.

A search method, a search system, and a natural language comprehension system are provided. The search system includes a structured database and a search engine. The structured database stores a plurality of records, each of which has a title field and a content field. The title field includes at least one sub-field, and each sub-field includes an indication field and a value field. The indication field stores indication data, the value field stores value data, and the content field stores detailed content data. The search engine conducts a full-text search to the records in the structured database according to a keyword derived from a user's request formation, and a search result is transmitted to a knowledge comprehension assistance module, so as to recognize the user's intention. After the user's intention is recognized, information associated with the recognized user's intention is transmitted back to the user.

The invention discloses a multi-round dialogue intelligent voice interaction system and device. The system comprises a hybrid semantic understanding module, a semantic understanding adaptive module and an automatic dialogue management module. The voice input is converted into a text and input to a hybrid semantic understanding module after being subjected to voice recognition; wherein the hybrid semantic understanding module is used for understanding user intention and extracting corresponding state information, an automatic dialogue management module is used for guiding a dialogue process, outputting dialogue texts and converting the dialogue texts into voice output based on the user intention to realize dialogue, and the semantic understanding self-adaptive module is used for optimized learning of the hybrid semantic understanding module. According to the invention, a plurality of modules such as speech recognition, natural language understanding, natural language generation, speechsynthesis and dialogue management are integrated to form a whole set of multi-round dialogue intelligent speech interaction system which is easy to expand and configure and can be applied to any scene.