Abstract: The present disclosure relates to a method for a dialog system. The method comprises: receiving a user input at the dialog system. A machine learning module may receive from the dialog system a dialog system response to the user input. In response to determining that the machine learning module is in a deactivated mode, selected one or more training data items of the dialog system response and the user input may be used for training the machine learning module. In response to determining that the machine learning module is in an active mode the trained machine learning module may estimate from the set of output data items and the user input a machine learning module response to the user input. The machine learning module response or the dialog system response may be provided.

Abstract: The present disclosure relates to a method for a dialog system. The method comprises: receiving a user input at the dialog system. A machine learning module may receive from the dialog system a dialog system response to the user input. In response to determining that the machine learning module is in a deactivated mode, selected one or more training data items of the dialog system response and the user input may be used for training the machine learning module. In response to determining that the machine learning module is in an active mode the trained machine learning module may estimate from the set of output data items and the user input a machine learning module response to the user input. The machine learning module response or the dialog system response may be provided.

Abstract: According to some aspects, a method of searching for content in response to a user voice query is provided. The method may comprise receiving the user voice query, performing speech recognition to generate N best speech recognition results comprising a first speech recognition result, performing a supervised search of at least one content repository to identify one or more supervised search results using one or more classifiers that classify the first speech recognition result into at least one class that identifies previously classified content in the at least one content repository, performing an unsupervised search of the at least one content repository to identify one or more unsupervised search results, wherein performing the unsupervised search comprises performing a word search of the at least one content repository, and generating combined results from among the one or more supervised search results and the one or more unsupervised search results.

Abstract: Methods, systems, computer-readable media, and apparatuses for providing search disambiguation using contextual information and domain ontologies are presented. In some embodiments, a computing device may receive a natural language input from a user. The computing device may identify a plurality of hypotheses for the natural language input. The computing device may map the plurality of hypotheses to one or more concepts of a plurality of concepts of an ontology by annotating the one or more concepts. The ontology may include the plurality of concepts respectively connected by a plurality of relations. The computing device may determine that there is an imperfect match between the annotated one or more concepts and annotations of answers. In response, the computing device may disambiguate the annotated one or more concepts using the ontology. The computing device may present output to the user based on the disambiguation.

Abstract: Techniques for error correction using a history list comprising at least one misrecognition and correction information associated with each of the at least one misrecognitions indicating how a user corrected the associated misrecognition. The techniques include converting data input from a user to generate a text segment, determining whether at least a portion of the text segment appears in the history list as one of the at least one misrecognitions, if the at least a portion of the text segment appears in the history list as one of the at least one misrecognitions, obtaining the correction information associated with the at least one misrecognition, and correcting the at least a portion of the text segment based, at least in part, on the correction information.

Abstract: Aspects described herein provide solutions to problems posed by a user. Input that includes a specified subject may be received from a user. A specified descriptor for the specified subject may be obtained from a hierarchical taxonomy associated with the specified subject. An information repository may be searched based on the specific descriptor, and entries stored at the information repository that are associated with the specific descriptor may be indicated in a list of results. The specific descriptor may be iteratively generalized to obtain generalized descriptors, and the information repository may be searched based on the generalized descriptors. The generalized descriptors may also be specialized to obtain specialized descriptors, and the information repository may be searched based on the specialized descriptors. The list of results may include entries stored at the information repository that are respectively associated with the generalized descriptors and the specialized descriptors.

Abstract: An automotive text display arrangement is described which includes a driver text display positioned directly in front of an automobile driver and displaying a limited amount of text to the driver without impairing forward visual attention of the driver. The arrangement may include a boundary insertion mode wherein when the active text position is an active text boundary, new text is inserted between the text items separated by the active text boundary, and when the active text position is an active text item, new text replaces the active text item. In addition or alternatively, there may be a multifunctional text control knob offering multiple different user movements, each performing an associated text processing function.

Abstract: Methods and apparatus to receive a first data stream, such as a public broadcast, and receive a second data stream, such as a private data stream, containing emails, for example. A user profile can be used to generate a data output stream for the user from the first and second data streams. The user profile can contain preferences for segments within the first and second data streams.

Abstract: Methods, devices, and computer program products for recognizing and responding to natural language input are described herein. Natural language input is received at a natural language input interface of a computing device and transformed into computer-usable text. A natural language input recognizer obtains evidence from one or more evidence source and generates an evidence graph based on the evidence obtained. Evidence may be obtained asynchronously, and the natural language input recognizer may update the evidence graph upon receipt of additional evidence. The natural language input recognizer generates a set of recognition hypotheses based on the evidence graph and selects one of the recognition hypotheses as a recognition result for the natural language input. Semantic models, evidence models, and response models may be employed to generate the evidence graph and respond to the recognition result selected for the natural language input.

Abstract: Methods and apparatus to receive a first data stream, such as a public broadcast, and receive a second data stream, such as a private data stream, containing emails, for example. A user profile can be used to generate a data output stream for the user from the first and second data streams. The user profile can contain preferences for segments within the first and second data streams.

Abstract: According to some aspects, a method of searching for content in response to a user voice query is provided. The method may comprise receiving the user voice query, performing speech recognition to generate N best speech recognition results comprising a first speech recognition result, performing a supervised search of at least one content repository to identify one or more supervised search results using one or more classifiers that classify the first speech recognition result into at least one class that identifies previously classified content in the at least one content repository, performing an unsupervised search of the at least one content repository to identify one or more unsupervised search results, wherein performing the unsupervised search comprises performing a word search of the at least one content repository, and generating combined results from among the one or more supervised search results and the one or more unsupervised search results.

Abstract: An automotive text display arrangement is described which includes a driver text display positioned directly in front of an automobile driver and displaying a limited amount of text to the driver without impairing forward visual attention of the driver. The arrangement may include a boundary insertion mode wherein when the active text position is an active text boundary, new text is inserted between the text items separated by the active text boundary, and when the active text position is an active text item, new text replaces the active text item. In addition or alternatively, there may be a multifunctional text control knob offering multiple different user movements, each performing an associated text processing function.

Abstract: An automotive text display arrangement is described which includes a driver text display positioned directly in front of an automobile driver and displaying a limited amount of text to the driver without impairing forward visual attention of the driver. The arrangement may include a boundary insertion mode wherein when the active text position is an active text boundary, new text is inserted between the text items separated by the active text boundary, and when the active text position is an active text item, new text replaces the active text item. In addition or alternatively, there may be a multifunctional text control knob offering multiple different user movements, each performing an associated text processing function.

Abstract: A textual message processing system and method are described for use in a mobile environment. A user messaging application processes at least one user textual message during a user messaging session. A semantic annotation module identifies one or more semantically salient terms in the user textual message, and annotates the user textual message with annotation terms having a low semantic distance to the semantically salient terms. A user message history stores the annotated textual messages. The semantic annotation module may further annotate the user textual message with situational meta-data characterizing the user textual message. There may be a message search module for using one or more keywords to search the user message history including the annotation terms, and identifying as a search match any annotated textual messages within a semantic distance threshold of the one or more keywords.

Abstract: Aspects described herein provide solutions to problems posed by a user. Input that includes a specified subject may be received from a user. A specified descriptor for the specified subject may be obtained from a hierarchical taxonomy associated with the specified subject. An information repository may be searched based on the specific descriptor, and entries stored at the information repository that are associated with the specific descriptor may be indicated in a list of results. The specific descriptor may be iteratively generalized to obtain generalized descriptors, and the information repository may be searched based on the generalized descriptors. The generalized descriptors may also be specialized to obtain specialized descriptors, and the information repository may be searched based on the specialized descriptors. The list of results may include entries stored at the information repository that are respectively associated with the generalized descriptors and the specialized descriptors.

Abstract: Systems and methods for multi-modal messaging that enable a user to compose, send and retrieve messages, such as SMS, MMS, IM or ordinary e-mail messages, for example, using one or more I/O (input/output) modalities (e.g., speech I/O and/or GUI I/O). A method for composing messages combines the advantages of a multi-modal interface (e.g., grammar-based speech and touchscreen or similar input devices) and message templates, which allows a user to construct a message with significantly less effort in a fraction of the time required by conventional methods. The user can dictate his/her messages using speech and/or GUI input, for example, based on a library of message templates which can be personalized by the user to fit his/her social interaction needs.

Abstract: Methods, devices, and computer program products for recognizing and responding to natural language input are described herein. Natural language input is received at a natural language input interface of a computing device and transformed into computer-usable text. A natural language input recognizer obtains evidence from one or more evidence source and generates an evidence graph based on the evidence obtained. Evidence may be obtained asynchronously, and the natural language input recognizer may update the evidence graph upon receipt of additional evidence. The natural language input recognizer generates a set of recognition hypotheses based on the evidence graph and selects one of the recognition hypotheses as a recognition result for the natural language input. Semantic models, evidence models, and response models may be employed to generate the evidence graph and respond to the recognition result selected for the natural language input.

Abstract: Techniques disclosed herein include systems and methods for managing user interface responses to user input including spoken queries and commands. This includes providing incremental user interface (UI) response based on multiple recognition results about user input that are received with different delays. Such techniques include providing an initial response to a user at an early time, before remote recognition results are available. Systems herein can respond incrementally by initiating an initial UI response based on first recognition results, and then modify the initial UI response after receiving secondary recognition results. Since an initial response begins immediately, instead of waiting for results from all recognizers, it reduces the perceived delay by the user before complete results get rendered to the user.

Abstract: Methods, systems, computer-readable media, and apparatuses for providing search disambiguation using contextual information and domain ontologies are presented. In some embodiments, a computing device may receive a natural language input from a user. The computing device may identify a plurality of hypotheses for the natural language input. The computing device may map the plurality of hypotheses to one or more concepts of a plurality of concepts of an ontology by annotating the one or more concepts. The ontology may include the plurality of concepts respectively connected by a plurality of relations. The computing device may determine that there is an imperfect match between the annotated one or more concepts and annotations of answers. In response, the computing device may disambiguate the annotated one or more concepts using the ontology. The computing device may present output to the user based on the disambiguation.

Abstract: A natural language query arrangement is described for a mobile environment. An automatic speech recognition (ASR) engine can process an unknown speech input from a user to produce corresponding recognition text. A natural language understanding module can extract natural language concept information classifier uses the from the recognition text. A query recognition text and the natural language concept information to assign to the speech input a query intent related to one or more objects in the mobile environment. An environment database contains information descriptive of objects in the mobile environment. A query search engine searches the environment database based on the query intent, the natural language concept information, and the recognition text to determine corresponding search results, which can be to the user.