Abstract: Provided are a system and method of mixing a second audio stream with a first audio stream in an audio output device. The system is configured to execute the method, comprising buffering and outputting the first audio stream via the audio output device as unmodified output, determining at least one insertion spot within the first audio stream, modifying the first audio stream at an insertion spot to avoid content loss, outputting the second audio stream at the insertion spot, and resuming unmodified output of the first audio stream at or near a completion of the second audio stream. Modifying the first audio stream can include pausing and/or warping the first audio stream at the insertion spot. The audio output device can be a vehicle head unit or a wireless device, such as a mobile phone.

Abstract: Provided are a system and method of input to a computer in a vehicle. An electronic communication is formed between a first electronic device and a display of a second electronic device that is viewable by a user from a location in the vehicle, including providing by the first electronic device a first input mode for the second electronic device. A multimodal application is executed that permits the user to interact with the display of the second electronic device by a combination of the first input mode and at least one second input mode for the second electronic device. The combination of the first input mode and the at least one second input mode controls the display of the first electronic device.

Abstract: A vehicle control system executing a voice control system for facilitating voice-based dialog with a driver to enable the driver or autonomous vehicle to control certain operational aspects of an autonomous vehicle is provided. Using environmental and sensor input, the vehicle control system can select optimal routes for operating the vehicle in an autonomous mode or choose a preferred operational mode. Occupants of the autonomous vehicle can change a destination, route or driving mode by engaging with the vehicle control system in a dialog enabled by the voice control system.

Abstract: A method, computer program product, and computing system for monitoring an interior environment of a motor vehicle; determining a personal state of an occupant within the interior environment of the motor vehicle; and interacting with the occupant based, at least in part, upon the personal state of the occupant.

Abstract: Some embodiments described herein relate to a multimodal user interface for use in an automobile. The multimodal user interface may display information on a windshield of the automobile, such as by projecting information on the windshield, and may accept input from a user via multiple modalities, which may include a speech interface as well as other interfaces. The other interfaces may include interfaces allowing a user to provide geometric input by indicating an angle. In some embodiments, a user may define a task to be performed using multiple different input modalities. For example, the user may provide via the speech interface speech input describing a task that the user is requesting be performed, and may provide via one or more other interfaces geometric parameters regarding the task. The multimodal user interface may determine the task and the geometric parameters from the inputs.

Abstract: A system, method and computer-readable storage device are disclosed for managing a mute and unmute feature on a device which is used to communicate data in a communication conference. The method includes detecting, when the device is set to mute, whether the user is speaking and whether the speech is meant for the conference. Background noises are distinguished from the speech of the user. If the user is speaking and the device is set to mute, the device will automatically switch to and unmute setting such that people in the indication conference can hear the user speak. Facial recognition, and gaze detection or other data can also be used to determine when to automatically mute or unmute the device and can aid in inferring an intent of the user to speak to the conference participants.

Abstract: Provided are a system and method of mixing a second audio stream with a first audio stream in an audio output device. The system is configured to execute the method, comprising buffering and outputting the first audio stream via the audio output device as unmodified output, determining at least one insertion spot within the first audio stream, modifying the first audio stream at an insertion spot to avoid content loss, outputting the second audio stream at the insertion spot, and resuming unmodified output of the first audio stream at or near a completion of the second audio stream. Modifying the first audio stream can include pausing and/or warping the first audio stream at the insertion spot. The audio output device can be a vehicle head unit or a wireless device, such as a mobile phone.

Abstract: Provided are a system and method of mixing a second audio stream with a first audio stream in an audio output device. The system is configured to execute the method, comprising buffering and outputting the first audio stream via the audio output device as unmodified output, determining at least one insertion spot within the first audio stream, modifying the first audio stream at an insertion spot to avoid content loss, outputting the second audio stream at the insertion spot, and resuming unmodified output of the first audio stream at or near a completion of the second audio stream. Modifying the first audio stream can include pausing and/or warping the first audio stream at the insertion spot. The audio output device can be a vehicle head unit or a wireless device, such as a mobile phone.

Abstract: A method, computer program product, and computing system for receiving a verbal command, from a user, on a vehicle infotainment system, wherein the vehicle infotainment system is configured to interface with an external system. A preferred system is identified for executing the verbal command. The verbal command is routed to the preferred system, wherein the preferred system is selected from the vehicle infotainment system and the external system.

Abstract: Techniques for generating language models. The techniques include: obtaining language data comprising training data and associated values for one or more metadata attributes, the language data comprising a plurality of instances of language data, an instance of language data comprising an instance of training data and one or more metadata attribute values associated with the instance of training data; identifying, by processing the language data using at least one processor, a set of one or more of the metadata attributes to use for clustering the instances of training data into a plurality of clusters; clustering the training data instances based on their respective values for the identified set of metadata attributes into the plurality of clusters; and generating a language model for each of the plurality of clusters.

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 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: Techniques for generating language models. The techniques include: obtaining language data comprising training data and associated values for one or more metadata attributes, the language data comprising a plurality of instances of language data, an instance of language data comprising an instance of training data and one or more metadata attribute values associated with the instance of training data; identifying, by processing the language data using at least one processor, a set of one or more of the metadata attributes to use for clustering the instances of training data into a plurality of clusters; clustering the training data instances based on their respective values for the identified set of metadata attributes into the plurality of clusters; and generating a language model for each of the plurality of clusters.

Abstract: Techniques for generating language models. The techniques include: obtaining language data comprising training data and associated values for one or more metadata attributes, the language data comprising a plurality of instances of language data, an instance of language data comprising an instance of training data and one or more metadata attribute values associated with the instance of training data; identifying, by processing the language data using at least one processor, a set of one or more of the metadata attributes to use for clustering the instances of training data into a plurality of clusters; clustering the training data instances based on their respective values for the identified set of metadata attributes into the plurality of clusters; and generating a language model for each of the plurality of clusters.

Abstract: Speech recognition systems often process speech by employing models and analyzing audio data. An embodiment of the method and corresponding system described herein allow for passive monitoring of, for example, conversation between user(s) to determine context to use to prime model(s) for later speech recognition requests submitted to the speech recognition system. The embodiment improves the results of the speech recognition system by updating speech recognition model(s) with contextual information of the conversation. This increases the probability that the speech recognition system interprets the conversation to contextually relevant information.

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.

Abstract: Speech recognition systems often process speech by employing models and analyzing audio data. An embodiment of the method and corresponding system described herein allow for passive monitoring of for example, conversation between user(s) to determine context to use to prime model(s) for later speech recognition requests submitted to the speech recognition system. The embodiment improves the results of the speech recognition system by updating speech recognition model(s) with contextual information of the conversation. This increases the probability that the speech recognition system interprets the conversation to contextually relevant information.

Abstract: A speech dialog system is described that adjusts a voice activity detection threshold during a speech dialog prompt to reflect a context-based probability of user barge in speech occurring. For example, the context-based probability may be based on the location of one or more transition relevance places in the speech dialog prompt.

Abstract: Techniques for generating language models. The techniques include: obtaining language data comprising training data and associated values for one or more metadata attributes, the language data comprising a plurality of instances of language data, an instance of language data comprising an instance of training data and one or more metadata attribute values associated with the instance of training data; identifying, by processing the language data using at least one processor, a set of one or more of the metadata attributes to use for clustering the instances of training data into a plurality of clusters; clustering the training data instances based on their respective values for the identified set of metadata attributes into the plurality of clusters; and generating a language model for each of the plurality of clusters.

Abstract: A speech dialog system is described that adjusts a voice activity detection threshold during a speech dialog prompt C to reflect a context-based probability of user barge in speech occurring. For example, the context-based probability may be based on the location of one or more transition relevance places in the speech dialog prompt.