Abstract: A cooperative conversational voice user interface is provided. The cooperative conversational voice user interface may build upon short-term and long-term shared knowledge to generate one or more explicit and/or implicit hypotheses about an intent of a user utterance. The hypotheses may be ranked based on varying degrees of certainty, and an adaptive response may be generated for the user. Responses may be worded based on the degrees of certainty and to frame an appropriate domain for a subsequent utterance. In one implementation, misrecognitions may be tolerated, and conversational course may be corrected based on subsequent utterances and/or responses.

Abstract: A cooperative conversational voice user interface is provided. The cooperative conversational voice user interface may build upon short-term and long-term shared knowledge to generate one or more explicit and/or implicit hypotheses about an intent of a user utterance. The hypotheses may be ranked based on varying degrees of certainty, and an adaptive response may be generated for the user. Responses may be worded based on the degrees of certainty and to frame an appropriate domain for a subsequent utterance. In one implementation, misrecognitions may be tolerated, and conversational course may be corrected based on subsequent utterances and/or responses.

Abstract: A cooperative conversational voice user interface is provided. The cooperative conversational voice user interface may build upon short-term and long-term shared knowledge to generate one or more explicit and/or implicit hypotheses about an intent of a user utterance. The hypotheses may be ranked based on varying degrees of certainty, and an adaptive response may be generated for the user. Responses may be worded based on the degrees of certainty and to frame an appropriate domain for a subsequent utterance. In one implementation, misrecognitions may be tolerated, and conversational course may be corrected based on subsequent utterances and/or responses.

Abstract: A cooperative conversational voice user interface is provided. The cooperative conversational voice user interface may build upon short-term and long-term shared knowledge to generate one or more explicit and/or implicit hypotheses about an intent of a user utterance. The hypotheses may be ranked based on varying degrees of certainty, and an adaptive response may be generated for the user. Responses may be worded based on the degrees of certainty and to frame an appropriate domain for a subsequent utterance. In one implementation, misrecognitions may be tolerated, and conversational course may be corrected based on subsequent utterances and/or responses.

Abstract: A conversational, natural language voice user interface may provide an integrated voice navigation services environment. The voice user interface may enable a user to make natural language requests relating to various navigation services, and further, may interact with the user in a cooperative, conversational dialogue to resolve the requests. Through dynamic awareness of context, available sources of information, domain knowledge, user behavior and preferences, and external systems and devices, among other things, the voice user interface may provide an integrated environment in which the user can speak conversationally, using natural language, to issue queries, commands, or other requests relating to the navigation services provided in the environment.

Abstract: A cooperative conversational voice user interface is provided. The cooperative conversational voice user interface may build upon short-term and long-term shared knowledge to generate one or more explicit and/or implicit hypotheses about an intent of a user utterance. The hypotheses may be ranked based on varying degrees of certainty, and an adaptive response may be generated for the user. Responses may be worded based on the degrees of certainty and to frame an appropriate domain for a subsequent utterance. In one implementation, misrecognitions may be tolerated, and conversational course may be corrected based on subsequent utterances and/or responses.

Abstract: A conversational, natural language voice user interface may provide an integrated voice navigation services environment. The voice user interface may enable a user to make natural language requests relating to various navigation services, and further, may interact with the user in a cooperative, conversational dialogue to resolve the requests. Through dynamic awareness of context, available sources of information, domain knowledge, user behavior and preferences, and external systems and devices, among other things, the voice user interface may provide an integrated environment in which the user can speak conversationally, using natural language, to issue queries, commands, or other requests relating to the navigation services provided in the environment.

Abstract: Embodiments that relate to identifying potential cross-language speech recognition problems are disclosed. For example, in one disclosed embodiment a speech recognition problem detection program receives a target word in a non-native language from a target application. A phonetic transcription of the target word comprising a plurality of target phonetic units is acquired. The program determines that at least one of the target phonetic units is not found in a plurality of native phonetic units associated with a native language. In response, a warning of the potential cross-language speech recognition problem may be outputted for display on a display device. The warning may comprise the target word.

Abstract: Embodiments are disclosed that relate to identifying phonetically similar speech grammar terms during computer program development. For example, one disclosed embodiment provides a method including providing a speech grammar development tool configured to receive input of a text representation of each of a plurality of proposed speech grammar terms, convert each text representation to a phonetic representation of the speech grammar term, compare the phonetic representation of the speech grammar term to the phonetic representations of other speech grammar terms using a weighted similarity matrix, and provide an output regarding risk of confusion between two proposed speech grammar terms based upon a comparison of the phonetic representations of the two proposed speech grammar terms. The method further includes receiving data regarding incorrect speech grammar term identification, and modifying one or more weights in the weighted similarity matrix based upon the data.

Abstract: Embodiments that relate to identifying potential cross-language speech recognition problems are disclosed. For example, in one disclosed embodiment a speech recognition problem detection program receives a target word in a non-native language from a target application. A phonetic transcription of the target word comprising a plurality of target phonetic units is acquired. The program determines that at least one of the target phonetic units is not found in a plurality of native phonetic units associated with a native language. In response, a warning of the potential cross-language speech recognition problem may be outputted for display on a display device. The warning may comprise the target word.

Abstract: Embodiments are disclosed that relate to identifying phonetically similar speech grammar terms during computer program development. For example, one disclosed embodiment provides a method including providing a speech grammar development tool configured to receive input of a text representation of each of a plurality of proposed speech grammar terms, convert each text representation to a phonetic representation of the speech grammar term, compare the phonetic representation of the speech grammar term to the phonetic representations of other speech grammar terms using a weighted similarity matrix, and provide an output regarding risk of confusion between two proposed speech grammar terms based upon a comparison of the phonetic representations of the two proposed speech grammar terms. The method further includes receiving data regarding incorrect speech grammar term identification, and modifying one or more weights in the weighted similarity matrix based upon the data.

Abstract: A cooperative conversational voice user interface is provided. The cooperative conversational voice user interface may build upon short-term and long-term shared knowledge to generate one or more explicit and/or implicit hypotheses about an intent of a user utterance. The hypotheses may be ranked based on varying degrees of certainty, and an adaptive response may be generated for the user. Responses may be worded based on the degrees of certainty and to frame an appropriate domain for a subsequent utterance. In one implementation, misrecognitions may be tolerated, and conversational course may be corrected based on subsequent utterances and/or responses.

Abstract: The system and method described herein may dynamically generate a recognition grammar associated with a conversational voice user interface in an integrated voice navigation services environment. In particular, in response to receiving a natural language utterance that relates to a navigation context at the voice user interface, a conversational language processor may generate a dynamic recognition grammar that organizes grammar information based on one or more topological domains. For example, the one or more topological domains may be determined based on a current location associated with a navigation device, whereby a speech recognition engine may use the grammar information organized in the dynamic recognition grammar according to the one or more topological domains to generate one or more interpretations associated with the natural language utterance.

Abstract: A conversational, natural language voice user interface may provide an integrated voice navigation services environment. The voice user interface may enable a user to make natural language requests relating to various navigation services, and further, may interact with the user in a cooperative, conversational dialogue to resolve the requests. Through dynamic awareness of context, available sources of information, domain knowledge, user behavior and preferences, and external systems and devices, among other things, the voice user interface may provide an integrated environment in which the user can speak conversationally, using natural language, to issue queries, commands, or other requests relating to the navigation services provided in the environment.

Abstract: The system and method described herein may dynamically generate a recognition grammar associated with a conversational voice user interface in an integrated voice navigation services environment. In particular, in response to receiving a natural language utterance that relates to a navigation context at the voice user interface, a conversational language processor may generate a dynamic recognition grammar that organizes grammar information based on one or more topological domains. For example, the one or more topological domains may be determined based on a current location associated with a navigation device, whereby a speech recognition engine may use the grammar information organized in the dynamic recognition grammar according to the one or more topological domains to generate one or more interpretations associated with the natural language utterance.

Abstract: A conversational, natural language voice user interface may provide an integrated voice navigation services environment. The voice user interface may enable a user to make natural language requests relating to various navigation services, and further, may interact with the user in a cooperative, conversational dialogue to resolve the requests. Through dynamic awareness of context, available sources of information, domain knowledge, user behavior and preferences, and external systems and devices, among other things, the voice user interface may provide an integrated environment in which the user can speak conversationally, using natural language, to issue queries, commands, or other requests relating to the navigation services provided in the environment.

Abstract: A cooperative conversational voice user interface is provided. The cooperative conversational voice user interface may build upon short-term and long-term shared knowledge to generate one or more explicit and/or implicit hypotheses about an intent of a user utterance. The hypotheses may be ranked based on varying degrees of certainty, and an adaptive response may be generated for the user. Responses may be worded based on the degrees of certainty and to frame an appropriate domain for a subsequent utterance. In one implementation, misrecognitions may be tolerated, and conversational course may be corrected based on subsequent utterances and/or responses.

Abstract: A cooperative conversational voice user interface is provided. The cooperative conversational voice user interface may build upon short-term and long-term shared knowledge to generate one or more explicit and/or implicit hypotheses about an intent of a user utterance. The hypotheses may be ranked based on varying degrees of certainty, and an adaptive response may be generated for the user. Responses may be worded based on the degrees of certainty and to frame an appropriate domain for a subsequent utterance. In one implementation, misrecognitions may be tolerated, and conversational course may be corrected based on subsequent utterances and/or responses.

Abstract: The system and method described herein may provide advertisements in an integrated voice navigation services environment. In particular, one or more advertisements may be identified based on affinities among a current location associated with a navigation device and shared knowledge and information used to interpret natural language utterances that relate to a navigation context, wherein the one or more advertisements may then be presented via a multi-modal output. As such, the shared knowledge and the information relating to the navigation context may provide the system and method with dynamic awareness relating to context, available information sources, domain knowledge, and user behavior and preferences, among other things, which may be used to deliver targeted and contextually relevant advertisements in the integrated navigation services environment.

Abstract: A conversational, natural language voice user interface may provide an integrated voice navigation services environment. The voice user interface may enable a user to make natural language requests relating to various navigation services, and further, may interact with the user in a cooperative, conversational dialogue to resolve the requests. Through dynamic awareness of context, available sources of information, domain knowledge, user behavior and preferences, and external systems and devices, among other things, the voice user interface may provide an integrated environment in which the user can speak conversationally, using natural language, to issue queries, commands, or other requests relating to the navigation services provided in the environment.