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257 results about "Natural language generation" patented technology

Natural-language generation (NLG) is a software process that transforms structured data into natural language. It can be used to produce long form content for organizations to automate custom reports, as well as produce custom content for a web or mobile application. It can also be used to generate short blurbs of text in interactive conversations (a chatbot) which might even be read out by a text-to-speech system.

Confidence-driven rewriting of source texts for improved translation

A method for rewriting source text includes receiving source text including a source text string in a first natural language. The source text string is translated with a machine translation system to generate a first target text string in a second natural language. A translation confidence for the source text string is computed, based on the first target text string. At least one alternative text string is generated, where possible, in the first natural language by automatically rewriting the source string. Each alternative string is translated to generate a second target text string in the second natural language. A translation confidence is computed for the alternative text string based on the second target string. Based on the computed translation confidences, one of the alternative text strings may be selected as a candidate replacement for the source text string and may be proposed to a user on a graphical user interface.
Owner:XEROX CORP

Systems and methods of detecting language and natural language strings for text to speech synthesis

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.
Owner:APPLE INC

Methods and systems for generating natural language descriptions from data

The invention is directed to a natural language generation (NLG) software system that generates rich, content-sensitive human language descriptions based on unparsed raw domain-specific data. In one embodiment, the NLG software system may include a data parser / normalizer, a comparator, a language engine, and a document generator. The data parser / normalizer may be configured to retrieve specification information for items to be described by the NLG software system, to extract pertinent information from the raw specification information, and to convert and normalize the extracted information so that the items may be compared specification by specification. The comparator may be configured to use the normalized data from the data parser / normalizer to compare the specifications of the items using comparison functions and interpretation rules to determine outcomes of the comparisons. The language engine may be configured to cycle through all or a subset of the normalized specification information, to retrieve all sentence templates associated with each of the item specifications, to call the comparator to compute or retrieve the results of the comparisons between the item specifications, and to recursively generate every possible syntactically legal sentence associated with the specifications based on the retrieved sentence templates. The document generator may be configured to select one or more discourse models having instructions regarding the selection, organization and modification of the generated sentences, and to apply the instructions of the discourse model to the generated sentences to generate a natural language description of the selected items.
Owner:CLASSIFIED VENTURES

Data driven natural language event detection and classification

ActiveUS20170357716A1Detection is relatively straightforwardNatural language data processingSound input/outputEvent typeUser device
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.
Owner:APPLE INC

In-context access of stored declarative knowledge using natural language expression

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).

Linguistically informed statistical models of constituent structure for ordering in sentence realization for a natural language generation system

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.
Owner:MICROSOFT TECH LICENSING LLC

Methods and systems for generating natural language descriptions from data

The invention is directed to a natural language generation (NLG) software system that generates rich, content-sensitive human language descriptions based on unparsed raw domain-specific data. In one embodiment, the NLG software system may include a data parser / normalizer, a comparator, a language engine, and a document generator. The data parser / normalizer may be configured to retrieve specification information for items to be described by the NLG software system, to extract pertinent information from the raw specification information, and to convert and normalize the extracted information so that the items may be compared specification by specification. The comparator may be configured to use the normalized data from the data parser / normalizer to compare the specifications of the items using comparison functions and interpretation rules to determine outcomes of the comparisons. The language engine may be configured to cycle through all or a subset of the normalized specification information, to retrieve all sentence templates associated with each of the item specifications, to call the comparator to compute or retrieve the results of the comparisons between the item specifications, and to recursively generate every possible syntactically legal sentence associated with the specifications based on the retrieved sentence templates. The document generator may be configured to select one or more discourse models having instructions regarding the selection, organization and modification of the generated sentences, and to apply the instructions of the discourse model to the generated sentences to generate a natural language description of the selected items.
Owner:CLASSIFIED VENTURES

Multi-round dialogue intelligent voice interaction system and device

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.
Owner:百融云创科技股份有限公司

System for natural language understanding

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.
Owner:GHANNAM RIMA +1

Natural language generation, a hybrid sequence-to-sequence approach

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.
Owner:CONDUENT BUSINESS SERVICES LLC

Access log analyzer and access log analyzing method

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.
Owner:C LIVE

Remote sensing image natural language generation method based on attention mechanism and deep learning

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.
Owner:JILIN UNIV

Sentence realization model for a natural language generation system

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.
Owner:MICROSOFT TECH LICENSING LLC

Method and apparatus for using directed reasoning to respond to natural language queries

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.
Owner:LEE RUSTY SHAWN +1

Hybrid approach for developing, optimizing, and executing conversational interaction applications

A system for hybrid approach to natural language understanding is provided, comprising a machine learning configured to create a new natural language understanding model from user-provided examples, and provide a natural language understanding model dataset to other components of the system; an integrated development environment configured to retrieve the natural language understanding model dataset, and publish a hybrid runtime solution; and an interaction engine configured to: retrieve the hybrid runtime solution, receive a natural language input, and process the natural language input and generate a log dataset; wherein, the log dataset may be used to retrain and improve existing models.
Owner:ARTIFICIAL SOLUTIONS

Natural language generation using pinned text and multiple discriminators

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.
Owner:JUNGLE DISK L L C

Automated contextual dialog generation for cognitive conversation

Systems and method for automated contextual dialog generation for cognitive conversations include embedding a natural language sentence input by a user into a corresponding sentence vector using a sentence embedder. A context array is generated using a contextual sentence embedder to embed the sentence vector and previous sentence vectors of a conversation history into a context array. Response words are predicted from the sentence vector by performing sequence-to-sequence dialog prediction with a dialog prediction network. Context of the input sentence is quantified by extracting context features from the context array using a situation quantification network. A response dialog is generated in natural language to display to a user, the response dialog responding to the input sentence with a response generator by determining a dialog state including the response words and the quantified context and optimizing the response dialog with reinforcement learning corresponding to the dialog state.
Owner:IBM CORP

Image target detection method based on natural language semantics

The invention discloses an image target detection method based on natural language semantics. Input of the method includes natural language phrase description of an image to be detected and a target to be detected; the image target detection method includes the steps that a global feature graph of the image to be detected is calculated through a convolutional neural network, then the global feature graph is input into an RPN network to calculate an alternative target set, a regional feature graph of an alternative target is extracted from the calculated alternative target set through an RoI pooling layer, the global feature graph of the image, the regional feature graph of the alternative target region and position information are used as context and combined with query phrase word vectors to represent input of an LSTM module and calculate the conditional probability of query phrases generated in the target region, and a detection result is returned according to the conditional probability. The natural language processing module LSTM model is fused into the Faster-RCNN frame, the shared computation characteristic of the Faster-RCNN frame and the image characteristics extraction advantage of the convolutional network are used for improving target detection efficiency and accuracy based on natural language semantics.
Owner:TSINGHUA UNIV

Medical interrogation dialogue system and reinforcement learning method applied to medical interrogation dialogue system

The invention discloses a medical interrogation dialogue system and a reinforcement learning method applied to the medical interrogation dialogue system, and relates to the technical field of medicalinformation. The system comprises a natural language understanding module used for classifying the intentions of users and filling slot values to form structured semantic frames; a dialogue managementmodule used for interacting with a user through a robot agent, inputting a dialogue state, performing action decision on the semantic frame through a decision network, and outputting final system action selection; a user simulator used for carrying out natural language interaction with the dialogue management module and outputting user action selection; a natural language generation module used for receiving system action selection and user action selection, enabling the user to check the selection through generating sentences similar to a human language by using a template-based method. According to the invention, the medical knowledge information between diseases and symptoms is introduced as a guide, and the inquiry historical experience is enriched through continuous interaction witha simulated patient. The reasonability of inquiry symptoms and the accuracy of disease diagnosis are improved, and the diagnosis result is higher in credibility.
Owner:暗物智能科技(广州)有限公司

Automated comprehension of natural language via constraint-based processing

A consistent meaning framework (CMF) graph including a plurality of nodes linked by a plurality of edges is maintained in data storage of a data processing system. Multiple nodes among the plurality of nodes are meaning nodes corresponding to different word meanings for a common word spelling of a natural language. Each of the multiple word meanings has a respective one of a plurality of associated constraints. A natural language communication is processed by reference to the CMF graph. The processing includes selecting, for a word in the natural language communication, a selected word meaning from among the multiple word meanings based on which of the plurality of associated constraints is satisfied by the natural language communication. An indication of the selected word meaning is stored in data storage.
Owner:VISEL THOMAS A

Method for processing natural language questions and apparatus thereof

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.
Owner:IBM CORP

Natural language data analytics platform

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.
Owner:ARTIFICIAL SOLUTIONS

Integration of domain information into state transitions of a finite state transducer for natural language processing

ActiveUS20160188573A1Precise alignmentEfficiently generate robust meaning representationNatural language translationSemantic analysisFinite state transducerApplication software
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.
Owner:VOICEBOX TECH INC

Computerized method of generating and analytically evaluating multiple instances of natural language-generated text

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.
Owner:CLOUDERA

Method and system context-aware for identifying, activating and executing software that best respond to user requests generated in natural language

InactiveUS20100004924A1Limiting its applicability and useReduce the potential mismatch for casesDigital data information retrievalNatural language data processingTypingText stream
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.
Owner:PAEZ YURI LUIS

Man-machine dialogue anomaly detection system and method

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.
Owner:AISPEECH CO LTD
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