561 results about "Natural language understanding" patented technology

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 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.

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 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 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.

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.

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 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 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.