Abstract: An automated arrangement is described for conducting natural language interactions with a human user. A user interface is provided for user communication in a given active natural language interaction with a natural language application during an automated dialog session. An automatic speech recognition (ASR) engine processes unknown user speech inputs from the user interface to produce corresponding speech recognition results. A natural language concept module processes the speech recognition results to develop corresponding natural language concept items. A concept item storage holds selected concept items for reuse in a subsequent natural language interaction with the user during the automated dialog session.

Abstract: A human-machine dialogue system is described which has multiple computer-implemented dialogue components. A user client delivers output prompts to a human user and receives dialogue inputs including speech inputs from the human user. An automatic speech recognition (ASR) engine processes the speech inputs to determine corresponding sequences of representative text words. A natural language understanding (NLU) engine processes the text words to determine corresponding semantic interpretations. A dialogue manager (DM) generates the output prompts and responds to the semantic interpretations so as to manage a dialogue process with the human user. The dialogue components share context information with each other using a common context sharing mechanism such that the operation of each dialogue component reflects available context information.

Abstract: A method of providing a custom response in conjunction with an application providing speech interaction is described. In one embodiment, the method comprises determining a context of a current interaction with the user, and identifying an associated custom animation, when the associated custom animation exists. The method further comprises displaying the custom animation by overlaying it over a native response of the application. In one embodiment, when no custom animation exists, the method determines whether there is a default animation, and displays the default animation as part of a state change of the application.

Abstract: An arrangement and corresponding method are described for multi-domain natural language processing. Multiple parallel domain pipelines are used for processing a natural language input. Each domain pipeline represents a different specific subject domain of related concepts. Each domain pipeline includes a mention module that processes the natural language input using natural language understanding (NLU) to determine a corresponding list of mentions, and an interpretation generator that receives the list of mentions and produces a rank-ordered domain output set of sentence-level interpretation candidates. A global evidence ranker receives the domain output sets from the domain pipelines and produces an overall rank-ordered final output set of sentence-level interpretations.

Abstract: An arrangement and corresponding method are described for distributed natural language processing. A set of local data sources is stored on a mobile device. A local natural language understanding (NLU) match module on the mobile device performs natural language processing of a natural language input with respect to the local data sources to determine one or more local interpretation candidates. A local NLU ranking module on the mobile device processes the local interpretation candidates and one or more remote interpretation candidates from a remote NLU server to determine a final output interpretation corresponding to the natural language input.

Abstract: An arrangement and corresponding method are described for natural language processing. A natural language understanding (NLU) arrangement processes a natural language input to determine a corresponding sentence-level interpretation. A user state component maintains user context data that characterizes an operating context of the NLU arrangement. Operation of the NLU arrangement is biased by the user context data.

Abstract: Some embodiments of the invention provide techniques for receiving a query from a user of a mobile device, and for conveying to the user not only search results, but also feedback relating to query. For example, the user may be prompted to elicit supplemental information relating to the query, or provided other feedback. The feedback may be conveyed in a manner which minimizes how much of the mobile device's display screen is dedicated to presenting the feedback.

Abstract: Some embodiments of the invention provide techniques for receiving a query from a user of a mobile device, and for conveying to the user not only search results, but also feedback relating to query. For example, the user may be prompted to elicit supplemental information relating to the query, or provided other feedback. The feedback may be conveyed in a manner which minimizes how much of the mobile device's display screen is dedicated to presenting the feedback.

Abstract: Some embodiments of the invention provide techniques for receiving a query from a user of a mobile device, and for conveying to the user not only search results, but also feedback relating to query. For example, the user may be prompted to elicit supplemental information relating to the query, or provided other feedback. The feedback may be conveyed in a manner which minimizes how much of the mobile device's display screen is dedicated to presenting the feedback.

Abstract: Some embodiments of the invention provide techniques for receiving a query from a user of a mobile device, and for conveying to the user not only search results, but also feedback relating to query. For example, the user may be prompted to elicit supplemental information relating to the query, or provided other feedback. The feedback may be conveyed in a manner which minimizes how much of the mobile device's display screen is dedicated to presenting the feedback.

Abstract: Some embodiments of the invention provide techniques for receiving a query from a user of a mobile device, and for conveying to the user not only search results, but also feedback relating to query. For example, the user may be prompted to elicit supplemental information relating to the query, or provided other feedback. The feedback may be conveyed in a manner which minimizes how much of the mobile device's display screen is dedicated to presenting the feedback.

Abstract: Some embodiments relate to techniques for receiving a query comprising content; in response to the query being received, determining that the content may have at least a first semantic meaning or a second semantic meaning that is different than the first semantic meaning; and identifying a plurality of search engines to which to submit a representation of the query, the plurality of search engines comprising a first search engine identified based on the first semantic meaning and a second search engine identified based on the second semantic meaning.

Abstract: A method of creating an application-generic class-based SLM includes, for each of a plurality of speech applications, parsing a corpus of utterance transcriptions to produce a first output set, in which expressions identified in the corpus are replaced with corresponding grammar tags from a grammar that is specific to the application. The method further includes, for each of the plurality of speech applications, replacing each of the grammar tags in the first output set with a class identifier of an application-generic class, to produce a second output set. The method further includes processing the resulting second output sets with a statistical language model (SLM) trainer to generate an application-generic class-based SLM.

Abstract: A method of creating an application-generic class-based SLM includes, for each of a plurality of speech applications, parsing a corpus of utterance transcriptions to produce a first output set, in which expressions identified in the corpus are replaced with corresponding grammar tags from a grammar that is specific to the application. The method further includes, for each of the plurality of speech applications, replacing each of the grammar tags in the first output set with a class identifier of an application-generic class, to produce a second output set. The method further includes processing the resulting second output sets with a statistical language model (SLM) trainer to generate an application-generic class-based SLM.

Abstract: A method and apparatus for generating a pair of data elements is provided suitable for use in a speaker verification system. The pair includes a first element representative of a speaker independent template and a second element representative of an extended speaker specific speech pattern. An audio signal forming enrollment data associated with a given speaker is received and processed to derive a speaker independent template and a speaker specific speech pattern. The speaker specific speech pattern is then processed to derive an extended speaker specific speech pattern. The extended speaker specific speech pattern includes a set of expanded speech models, each expanded speech model including a plurality of groups of states, the groups of states being linked to one another by inter-group transitions. Optionally, the expanded speech models are processed on the basis of the enrollment data to condition at least one of the plurality of inter-group transitions.

Abstract: A method and apparatus for use in the field of speaker verification. The invention provides a method and apparatus for generating a pair of data elements, namely a first element representative of a speaker specific speech pattern and a second element representative of a biased normalizing template, the pair of data elements being suitable for use in a speaker verification system. The invention provides receiving an audio signal representative of a training token associated with a given speaker and processing the training token on a basis of a reference speaker independent model set to derive a speaker independent normalizing template. The invention further provides processing the training token on a basis of a reference speaker independent model set for generating a speaker specific speech pattern. The speaker specific speech pattern and the speaker independent normalizing template are then processed to derive a biased normalizing template.