An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

Intelligent Automated Assistant

Systems and methods are provided for receiving speech and non-speech communications of natural language questions and/or commands, transcribing the speech and non-speech communications to textual messages, and executing the questions and/or commands. The invention applies context, prior information, domain knowledge, and user specific profile data to achieve a natural environment for one or more users presenting questions or commands across multiple domains. The systems and methods creates, stores and uses extensive personal profile information for each user, thereby improving the reliability of determining the context of the speech and non-speech communications and presenting the expected results for a particular question or command.

Systems and methods for responding to natural language speech utterance

A method and system to search a variety of types of documents for material related to concepts expressed in a natural language text. The invention includes analyzing the natural language text to determine an underlying concept (420) and identifying one or more categories (430) of searchable material in a knowledge base that are related to the underlying concept. The invention includes intelligently providing documents from the knowledge base (480) in these categories, both automatically and with the assistance of a customer service agent.

Intelligent data search

A mobile system is provided that includes speech-based and non-speech-based interfaces for telematics applications. The mobile system identifies and uses context, prior information, domain knowledge, and user specific profile data to achieve a natural environment for users that submit requests and/or commands in multiple domains. The invention creates, stores and uses extensive personal profile information for each user, thereby improving the reliability of determining the context and presenting the expected results for a particular question or command. The invention may organize domain specific behavior and information into agents, that are distributable or updateable over a wide area network.

Mobile systems and methods of supporting natural language human-machine interactions

A virtual assistant uses context information to supplement natural language or gestural input from a user. Context helps to clarify the user's intent and to reduce the number of candidate interpretations of the user's input, and reduces the need for the user to provide excessive clarification input. Context can include any available information that is usable by the assistant to supplement explicit user input to constrain an information-processing problem and/or to personalize results. Context can be used to constrain solutions during various phases of processing, including, for example, speech recognition, natural language processing, task flow processing, and dialog generation.

Using context information to facilitate processing of commands in a virtual assistant

A computer-implemented method and system for speech recognition of a user speech input. The user speech input which contains utterances from a user is received. A first language model recognizes at least a portion of the utterances from the user speech input. The first language model has utterance terms that form a general category. A second language model is selected based upon the identified utterances from use of the first language model. The second language model contains utterance terms that are a subset category of the general category of utterance terms in the first language model. Subset utterances are recognized with the selected second language model from the user speech input.

Computer-implemented multi-scanning language method and system

A computer-implemented speech recognition method and system for handling noise contained in a user input speech. The user input speech from a user contains environmental noise, user vocalized noise, and useful sounds. A domain acoustic noise model is selected from a plurality of candidate domain acoustic noise models that substantially matches the acoustic profile of the environmental noise in the user input speech. Each of the candidate domain acoustic noise models contains a noise acoustic profile specific to a pre-selected domain. An environmental noise language model is adjusted based upon the selected domain acoustic noise model and is used to detect the environmental noise within the user input speech. A vocalized noise model is adjusted based upon the selected domain acoustic noise model and is used to detect the vocalized noise within the user input speech. A language model is adjusted based upon the selected domain acoustic noise model and is used to detect the useful sounds within the user input speech. Speech recognition is performed upon the user input speech using the adjusted environmental noise language model, the adjusted vocalized noise model, and the adjusted language model.

Computer-implemented noise normalization method and system

A computer-implemented system and method for processing speech input from a user. A call management unit receives a call from the user and through which the speech input is provided by the user. A speech management unit recognizes the user speech input through language recognition models. The language recognition models contains word recognition probability data derived from word usage on Internet web pages. A service management unit handles e-commerce requests contained in the user speech input. A web data management unit connected to an Internet network processes Internet web pages in order to generate the language recognition models for the speech management unit and to generate a summary of the Internet web pages. The generated summary is voiced to the user in order to service the user request.

Dialogue application computer platform

A computer-implemented system and method for speech recognition of a user speech input. A language model is used to contain probabilities used to recognize speech, and an application domain description data store contains a mapping between pre-selected words and domains. A probability adjustment unit selects at least one domain based upon the user speech input. The probability adjustment unit adjusts the probabilities of the language model to recognize the user speech input based upon the words that are mapped to the selected domain.

Computer-implemented speech expectation-based probability method and system

A computer-implemented method and system for generating speech models for use in speech recognition of a user speech input. Word conceptual networks are formed by grouping words with pre-selected pivot words. The groupings of words form phrases directed to pre-selected concepts. Phoneme networks are associated with the words in the word conceptual networks. The phoneme networks contain probabilities for recognizing the words in the word conceptual networks. A language model is partitioned into sub-language models based upon the pivot words. The sub-language models include the phoneme networks that are associated with the words grouped with the sub-language models' respective pivot words.

Computer-implemented intelligent speech model partitioning method and system

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