252 results about "Natural language generation" patented technology

Algorithms for synthesizing speech used to identify media assets are provided. Speech may be selectively synthesized form text strings associated with media assets. A text string may be normalized and its native language determined for obtaining a target phoneme for providing human-sounding speech in a language (e.g., dialect or accent) that is familiar to a user. The algorithms may be implemented on a system including several dedicated render engines. The system may be part of a back end coupled to a front end including storage for media assets and associated synthesized speech, and a request processor for receiving and processing requests that result in providing the synthesized speech. The front end may communicate media assets and associated synthesized speech content over a network to host devices coupled to portable electronic devices on which the media assets and synthesized speech are played back.

Systems and processes for operating a digital assistant are provided. In accordance with one or more examples, a method includes, at a user device with one or more processors and memory, receiving unstructured natural language information from at least one user. The method also includes, in response to receiving the unstructured natural language information, determining whether event information is present in the unstructured natural language information. The method further includes, in accordance with a determination that event information is present within the unstructured natural language information, determining whether an agreement on an event is present in the unstructured natural language information. The method further includes, in accordance with a determination that an agreement on an event is present, determining an event type of the event and providing an event description based on the event type.

Identifying a context for parsing a natural language expression. In an embodiment, a table comprising rows addressed according to context compartments is disclosed. Each compartment represents a context and comprises row(s), and each row represents a concept and comprises an outline field indicating an order of the concept in its context. Input expression(s) are received, and a first search is performed on the table to identify rows representing concepts corresponding to element(s) of the expression(s) and rows representing concepts corresponding to combinations of concepts represented by previously identified rows until a first row representing a higher-order concept is identified. Based on the first row, a first context compartment is determined, and a second search, that is restricted to the first context compartment, is performed to identify a second row representing a concept corresponding to an entirety of at least one of the input expression(s).

The present invention is a tree ordering component within a sentence realization system which receives an unordered syntax tree and generates a ranked list of alternative ordered syntax trees from the unordered syntax tree. The present invention also includes statistical models of constituent structure employed by the tree ordering component in scoring the alternative ordered trees.

A general-purpose apparatus for analyzing natural language text that allows for the implementation of a broad range of natural language understanding applications. The apparatus for natural language understanding analyzes a source text and transforms the source text into a semantically-interpretable syntactic representation (SISR), comprising a syntax template and semantic clause annotations. The general-purpose apparatus for natural language understanding is adaptable to various source text natural languages and is adaptable to various natural language understanding applications, such as query answering, translation, summarization, information extraction, disambiguation, and parsing. A natural language query answering apparatus for answering questions about a source text, whereby the query answering apparatus utilizes the general-purpose apparatus for transforming the natural language query into SISR format.

A method and method for natural language generation employ a natural language generation model which has been trained to assign an utterance label to a new text sequence, based on features extracted from the text sequence, such as parts-of-speech. The model assigns an utterance label to the new text sequence, based on the extracted features. The utterance label is used to guide the generation of a natural language utterance, such as a question, from the new text sequence. The system and method find application in dialog systems for generating utterances, to be sent to a user, from brief descriptions of problems or solutions in a knowledge base.

An access log analyzer extracts significant information from an enormous amount of data of access logs of a Web server so as to appropriately display the result of analysis. The access log analyzer includes an FTP module for acquiring a log from a server to be analyzed, a pre-formatting module for pre-processing the acquired log, a pre-counting module for totaling preformatted data for each monitored item, a main diagnostic statement creating module for creating a main diagnostic statement for the monitored item of the pre-counted data, a sub-diagnostic statement creating module for creating a sub-diagnostic statement for data related to the main diagnostic statement, a diagnostic statement connecting module for connecting the diagnostic statements, and a dispatcher module for managing the execution of each of the modules. The diagnostic statement creating modules have the functions of calculating a Z value for a diagnosed item and then generating a diagnostic statement in a natural language if there is a variation larger than usual with reference to a diagnostic parameter describing a model of a diagnostic statement corresponding to the range of the Z value.

The invention relates to a remote sensing image natural language generation method based on an attention mechanism and deep learning. The method comprises the steps of first, preprocessing a remote sensing image and corresponding natural language description; second, inputting the denoised remote sensing image into an intensive positioning convolution neural network (IPCNN); third, inputting region blocks obtained in the second step into a reassignment long-short term memory (RLSTM) network, getting into a weight assignment layer of the RLSTM network, respectively solving the weight of each region by using a multilayer network function, and finally realizing overall output of the natural language description through a deep output layer of the RLSTM network; fourth, inputting the natural language description generated in the third step into a remote sensing image language description scoring model to obtain a score of each sentence; and fifth, inputting a target position, a category label and a natural language description score into a database to wait for calling.

The present invention is a sentence realization system that processes an abstract linguistic representation (ALR) of a sentence into a structure that can be fully realizable. The system includes a tree conversion component that receives the ALR and generates a basic syntax tree from the ALR. A global movement component then receives the basic syntax tree and hierarchically orders child nodes in that syntax tree relative to ancestor nodes. An intra-constituent ordering component then establishes a linear order among the nodes such that the syntax tree is fully ordered. A surface cleanup component receives the fully ordered tree and performs a number of realization operations to generate surface realizations for constituents that are still represented in an abstract way in the fully ordered syntax tree.

A method and apparatus are presented for using directed reasoning to provide natural language responses to questions and commands in natural language. The directed reasoning process uses concepts in the natural language sentence to identify relevant response concepts in a knowledge base, by creating a continuous chain of logic from the input concept to the response concept and limiting the creation of the logic chains to only those consistent with the context of the natural language sentence and information in the knowledge base. The invention allows the identification of relevant concepts that elude traditional concept searching based on pattern matching, while focusing computational resources on only those logic calculations relevant to the natural language sentence and knowledge base. The invention will automatically identify the relevant source documents to use and create a knowledge base during run time, without requiring preprogrammed ontologies or knowledge bases.

A personality model is created for a population and used as an input to a text generation system. Alternative texts are created based upon the emotional effect of the generated text. Certain words or phrases are “pinned” in the output, reducing the variability of the generated text so as to preserve required information content, and a number of tests provide input to a discriminator network so that proposed outputs both match an outside objective regarding the information content, emotional affect, and grammatical acceptability. A feedback loop provides new “ground truth” data points for refining the personality model and associated generated text.

A method and an apparatus for selecting an answer to a natural language question. The method includes: detecting a named entity in the natural language question; extracting information related to an answer from the natural language question; searching in linked data according to the detected named entity; generating a candidate answer according to a search result; parsing the candidate answer according to the information related to the answer; and obtaining a value of a feature of the candidate answer; and evaluating each candidate answer by synthesizing the value of the feature of the candidate answer.

A system for natural language analytics, stored and operating on a network-connected computing device, comprising a natural language application data importer, further comprising a natural language application data importer, a natural language application data augmenter that enriches the data and an analytics component which provides a means of querying structured as well as unstructured data and which also contains a method for providing adaptive natural language analytics.

The invention relates to a system and method for integrating domain information into state transitions of a Finite State Transducer (“FST”) for natural language processing. A system may integrate semantic parsing and information retrieval from an information domain to generate an FST parser that represents the information domain. The FST parser may include a plurality of FST paths, at least one of which may be used to generate a meaning representation from a natural language input. As such, the system may perform domain-based semantic parsing of a natural language input, generating more robust meaning representations using domain information. The system may be applied to a wide range of natural language applications that use natural language input from a user such as, for example, natural language interfaces to computing systems, communication with robots in natural language, personalized digital assistants, question-answer query systems, and/or other natural language processing applications.

A computerized method for generating and evaluating natural language-generated text involves receiving, in a computer, data input by a user, generating, using a natural language generation technique, multiple instances of text stories based upon both contents of a corpus and the received data; analyzing the multiple instances of text stories as a weighted combination of computed geographic scores, distance scores, information content scores, replacement scores and extra aspect scores, providing a ranked set of the generated text stories to a user, receiving a selection of one of the text stories in the ranked set, and storing the selected story.

A computer-implemented method capable of identifying, activating, and executing commands, methods, functions, interfaces, and software-based applications that can satisfy a specific natural language user request represented by a text stream and generated from any means such as typing, voice, gestures, signs or by human thoughts.

A method is provided for generating automated responses to customer questions. Terms of a customer question are received, which are then decomposed into components of the question. An intent is determined from at least one of the components. A query is formulated with the intent. The query is searched in a plurality of data sources to obtain raw search results. These raw search results are compared, and those results proximate to the intent are selected. After redundant and non-informative results are removed, these proximate search results are stored in a cache. The cache is further analyzed/processed to eliminate redundant parts. At least one of natural language understanding (NLU), natural language generation (NLG) or generative neural nets (GNN) is applied to the remaining text in the cache to generate a natural language answer to the customer question.

Provided is a man-machine dialogue anomaly detection system and method. The method includes steps: acquiring and marking historical dialogue data, training an anomaly detection model by employing the marked data, conducting anomaly detection by employing the trained anomaly detection model when receiving real-time dialogue data, and obtaining a result. The system comprises an automatic speech recognition module (ASR module), a text-to-speech module (TTS module), a spoken language understanding module (SLU module), a dialogue state tracking module (DST module), a dialogue management module (DM module), a database query module (DATA module), a natural language generation module (NLG module), and an anomaly detection and processing module. According to the system and method, replies given by a machine can be reliable, and the system and method can be applied to any scene.