Abstract: Particular embodiments described herein provide for an electronic device that can be configured to receive a verbal command to active a device with an unknown label, derive a probable device and a label for the probable device, activate the probable device, determine that the activated probable device is the same device to be activated by the verbal command, and store the label and a description for the device. In some examples, the label is associated with the description.

Abstract: Particular embodiments described herein provide for an electronic device that can be configured to communicate information to a user using a first style of communication, receive language-based communication from the user, and determine that the language-based communication indicates a desire of the user to change from the first style of communication to a second style of communication.

Abstract: Particular embodiments described herein provide for an electronic device that can be configured to receive a verbal command to active a device with an unknown label, derive a probable device and a label for the probable device, activate the probable device, determine that the activated probable device is the same device to be activated by the verbal command, and store the label and a description for the device. In some examples, the label is associated with the description.

Abstract: Embodiments are directed to systems, methods, and devices for providing help to a user through an output modality. Embodiments include an analysis logic implemented at least partially in hardware to receive an indication to provide help or other information to the user; identify an availability of one or more output modalities for providing the help; and determine an output modality for providing the help based on the availability of the one or more output modalities. Embodiments also include a dialog system implemented at least partially in hardware to process the request for help; and provide a dialog message in response to the request for help, the dialog message provided on the determined output modality. Some embodiments also include a sensor input for receiving sensory information, wherein the analysis logic identifies the output modality based, at least in part, on the sensory information.

Abstract: The present disclosure describes providing a biometric signal as an input to a dialog system. A biometric signal processor can derive contextual biometric information about the biometric signal based on stored information and received, user-provided information. The dialog system can be used to interface with a user to receive contextual data about the user's status or activities, and can be used to interact with the user to request information and provide the contextualized biometric information.

Abstract: The present disclosure describes dynamically adjusting linguistic models for automatic speech recognition based on biometric information to produce a more reliable speech recognition experience. Embodiments include receiving a speech signal, receiving a biometric signal from a biometric sensor implemented at least partially in hardware, determining a linguistic model based on the biometric signal, and processing the speech signal for speech recognition using the linguistic model based on the biometric signal.

Abstract: Embodiments are directed to systems, methods, and devices that are directed to a sensor implemented at least partially in hardware to detect information about a user and a processor implemented at least partially in hardware to determine a state of the user based on the detected information, and select an output mode for a dialog message based on the state of the user. A dialog system implemented at least partially in hardware can be included to configure a dialog message based on the selected output mode; and output the dialog message to the user.

Abstract: Methods and computer-readable media for associating words or groups of words distilled from content, such as reported speech or an attitude report, of a document to form semantic relationships collectively used to generate a semantic representation of the content are provided. Semantic representations may include elements identified or parsed from a text portion of the content, the elements of which may be associated with other elements that share a semantic relationship, such as an agent, location, or topic relationship. Relationships may also be developed by associating one element that is in relation to, or is about, another element, thereby allowing for rapid and effective comparison of associations found in a semantic representation with associations derived from queries. The semantic relationships may be determined based on semantic information, such as potential meanings and grammatical functions of each element within the text portion of the content.

Abstract: Methods and computer-readable media for associating words or groups of words distilled from content, such as reported speech or an attitude report, of a document to form semantic relationships collectively used to generate a semantic representation of the content are provided. Semantic representations may include elements identified or parsed from a text portion of the content, the elements of which may be associated with other elements that share a semantic relationship, such as an agent, location, or topic relationship. Relationships may also be developed by associating one element that is in relation to, or is about, another element, thereby allowing for rapid and effective comparison of associations found in a semantic representation with associations derived from queries. The semantic relationships may be determined based on semantic information, such as potential meanings and grammatical functions of each element within the text portion of the content.

Abstract: Methods and computer-readable media for associating words or groups of words distilled from content, such as reported speech or an attitude report, of a document to form semantic relationships collectively used to generate a semantic representation of the content are provided. Semantic representations may include elements identified or parsed from a text portion of the content, the elements of which may be associated with other elements that share a semantic relationship, such as an agent, location, or topic relationship. Relationships may also be developed by associating one element that is in relation to, or is about, another element, thereby allowing for rapid and effective comparison of associations found in a semantic representation with associations derived from queries. The semantic relationships may be determined based on semantic information, such as potential meanings and grammatical functions of each element within the text portion of the content.

Abstract: Technologies are described herein for coreference resolution in an ambiguity-sensitive natural language processing system. Techniques for integrating reference resolution functionality into a natural language processing system can processes documents to be indexed within an information search and retrieval system. Ambiguity awareness features, as well as ambiguity resolution functionality, can operate in coordination with coreference resolution. Annotation of coreference entities, as well as ambiguous interpretations, can be supported by in-line markup within text content or by external entity maps. Information expressed within documents can be formally organized in terms of facts, or relationships between entities in the text. Expansion can support applying multiple aliases, or ambiguities, to an entity being indexed so that all of the possibly references or interpretations for that entity are captured into the index.

Abstract: Computer-readable media and a computer system for implementing a natural language search using fact-based structures and for generating such fact-based structures are provided. A fact-based structure is generated using a semantic structure, which represents information, such as text, from a document, such as a web page. Typically, a natural language parser is used to create a semantic structure of the information, and the parser identifies terms, as well as the relationship between the terms. A fact-based structure of a semantic structure allows for a linear structure of these terms and their relationships to be created, while also maintaining identifiers of the terms to convey the dependency of one fact-based structure on another fact-based structure. Additionally, synonyms and hypernyms are identified while generating the fact-based structure to improve the accuracy of the overall search.

Abstract: Tools and techniques related to calculating valence of expressions within documents. These tools may provide methods that include receiving input documents for processing, and extracting expressions from the documents for valence analysis, with scope relationships occurring between terms contained in the expressions. The methods may calculate calculating valences of the expressions, based on the scope relationships between terms in the expressions.

Abstract: Technologies are described herein for generating a semantic translation rule to support natural language search. In one method, a first expression and a second expression are received. A first representation is generated based on the first expression, and a second representation is generated based on the second expression. Aligned pairs of a first term in the first representation and a second term in the second representation are determined. For each aligned pair, the first term and the second term are replaced with a variable associated with the aligned pair. Word facts that occur in both the first representation and the second representation are removed from the first representation and the second representation. The remaining word facts in the first representation are replaced with a broader representation of the word facts. The translation rule including the first representation, an operator, and the second semantic representation is generated.

Abstract: Techniques are provided to determine service data features from an archive of web service transactions. Data features for functionally identical classes of service are determined. Differentiating data feature patterns uniquely identifying each service within the class are learned using machine learning, clustering, statistical analysis and the like. A service map associating services with the differentiating patterns is determined. The service map contains data feature patterns that differentiate among otherwise functionally identical services. The data features are optionally associated with past usage, objective and subjective service quality measurements and the like. The data features of the received service requests are compared to differentiating patterns in the service map. The service associated with the differentiating patterns matching the data features of the service request is selected.

Abstract: Techniques are provided for determining collaborative notes and automatically recognizing speech, handwriting and other type of information. Domain and optional actor/speaker information associated with the support information is determined. An initial automatic speech recognition model is determined based on the domain and/or actor information. The domain and/or actor/speaker language model is used to recognize text in the speech information associated with the support information. Presentation support information such as slides, speaker notes and the like are determined. The semantic overlap between the support information and the salient non-function words in the recognized text and collaborative user feedback information are used to determine relevancy scores for the recognized text. Grammaticality, well formedness, self referential integrity and other features are used to determine correctness scores.

Abstract: Techniques are provided for determining collaborative notes and automatically recognizing speech, handwriting and other type of information. Domain and optional actor/speaker information associated with the support information is determined. An initial automatic speech recognition model is determined based on the domain and/or actor information. The domain and/or actor/speaker language model is used to recognize text in the speech information associated with the support information. Presentation support information such as slides, speaker notes and the like are determined. The semantic overlap between the support information and the salient non-function words in the recognized text and collaborative user feedback information are used to determine relevancy scores for the recognized text. Grammaticality, well formedness, self referential integrity and other features are used to determine correctness scores.

Abstract: Technologies are described herein for generating a semantic translation rule to support natural language search. In one method, a first expression and a second expression are received. A first representation is generated based on the first expression, and a second representation is generated based on the second expression. Aligned pairs of a first term in the first representation and a second term in the second representation are determined. For each aligned pair, the first term and the second term are replaced with a variable associated with the aligned pair. Word facts that occur in both the first representation and the second representation are removed from the first representation and the second representation. The remaining word facts in the first representation are replaced with a broader representation of the word facts. The translation rule including the first representation, an operator, and the second semantic representation is generated.

Abstract: Technologies are described herein for coreference resolution in an ambiguity-sensitive natural language processing system. Techniques for integrating reference resolution functionality into a natural language processing system can processes documents to be indexed within an information search and retrieval system. Ambiguity awareness features, as well as ambiguity resolution functionality, can operate in coordination with coreference resolution. Annotation of coreference entities, as well as ambiguous interpretations, can be supported by in-line markup within text content or by external entity maps. Information expressed within documents can be formally organized in terms of facts, or relationships between entities in the text. Expansion can support applying multiple aliases, or ambiguities, to an entity being indexed so that all of the possibly references or interpretations for that entity are captured into the index.

Abstract: Tools and techniques related to calculating valence of expressions within documents. These tools may provide methods that include receiving input documents for processing, and extracting expressions from the documents for valence analysis, with scope relationships occurring between terms contained in the expressions. The methods may calculate calculating valences of the expressions, based on the scope relationships between terms in the expressions.