Abstract: A vehicle system for classifying spoken utterance within a vehicle cabin as one of system-directed and non-system directed may include at least one microphone to detect at least one acoustic utterance from at least one occupant of the vehicle, at least one camera to detect occupant data indicative of occupant behavior within the vehicle corresponding to the acoustic utterance, and a processor programmed to receive the acoustic utterance, receive the occupant data, determine whether the occupant data is indicative of a vehicle feature, classify the acoustic utterance as a system-directed utterance in response to the occupant data being indicative of a vehicle feature, and process the acoustic utterance.

Abstract: A haptic-communication system includes a fabric, a frame that supports the fabric, and a haptic element that is integral with a textile that forms the fabric. A transition of the haptic element between first and second states thereof provides communication with a person in contact with the haptic element.

Abstract: According to some aspects, a method of monitoring an acoustic environment of a mobile device, at least one computer readable medium encoded with instructions that, when executed, perform such a method and/or a mobile device configured to perform such a method is provided. The method comprises receiving acoustic input from the environment of the mobile device while the mobile device is operating in the low power mode, detecting whether the acoustic input includes a voice command based on performing a plurality of processing stages on the acoustic input, wherein at least one of the plurality of processing stages is performed while the mobile device is operating in the low power mode, and using at least one contextual cue to assist in detecting whether the acoustic input includes a voice command.

Abstract: A method for selecting a speech recognition result on a computing device includes receiving a first speech recognition result determined by the computing device, receiving first features, at least some of the features being determined using the first speech recognition result, determining whether to select the first speech recognition result or to wait for a second speech recognition result determined by a cloud computing service based at least in part on the first speech recognition result and the first features.

Abstract: A system and method of responding to a vocal utterance may include capturing and converting the utterance to word(s) using a language processing method, such as natural language processing. The context of the utterance and of the system, which may include multimodal inputs, may be used to determine the meaning and intent of the words.

Abstract: According to some aspects, a system for detecting a designated wake-up word is provided, the system comprising a plurality of microphones to detect acoustic information from a physical space having a plurality of acoustic zones, at least one processor configured to receive a first acoustic signal representing the acoustic information received by the plurality of microphones, process the first acoustic signal to identify content of the first acoustic signal originating from each of the plurality of acoustic zones, provide a plurality of second acoustic signals, each of the plurality of second acoustic signals substantially corresponding to the content identified as originating from a respective one of the plurality of acoustic zones, and performing automatic speech recognition on each of the plurality of second acoustic signals to determine whether the designated wake-up word was spoken.

Abstract: A user device configured to perform wake-up word detection in a target language.

Abstract: According to some aspects, a method of monitoring an acoustic environment of a mobile device, at least one computer readable medium encoded with instructions that, when executed, perform such a method and/or a mobile device configured to perform such a method is provided. The method comprises receiving acoustic input from the environment of the mobile device while the mobile device is operating in the low power mode, detecting whether the acoustic input includes a voice command based on performing a plurality of processing stages on the acoustic input, wherein at least one of the plurality of processing stages is performed while the mobile device is operating in the low power mode, and using at least one contextual cue to assist in detecting whether the acoustic input includes a voice command.

Abstract: A system for integrating disparate ecosystems including smart home and internet-of-things (IoT) ecosystems. The system including a vehicle assistant that executes within the context of a cloud-based application and that retrieves sensor data and utterances from a vehicle and forwards the sensor data and passenger-spoken utterances to a cloud-based application. Using the sensor data and utterances, the cloud-based application selects and executes a predetermined routine that includes at least one action to be completed in vehicle, on mobile phone or Smart Home/IoT ecosystem. The action is then complete by issuing the command to the vehicle head-unit, specified mobile phone or target ecosystem selected from a group of disparate ecosystems.

Abstract: A system for routing commands issued by a passenger of a vehicle to a Smart Home and/or an Internet of Things (IoT) ecosystem via a connection manager. Issued commands are obtained from utterances using speech recognition and analyzed using natural language understanding and natural language processing. Using the output of the natural understanding analysis, the connection manager determines where to send the command by identifying a target Smart Home and/or IoT ecosystem.

Abstract: Methods and an apparatus for performing feature extraction on speech in a microphone signal with embedded noise processing to reduce the amount of processing are provided. In embodiments, feature extraction and the noise estimate use an output of the same Fourier Transform, such that the noise filtering of the speech is embedded with the feature extraction of the speech.

Abstract: While current voice assistants can respond to voice requests, creating smarter assistants that leverage location, past requests, and user data to enhance responses to future requests and to provide robust data about locations is desirable. A method for enhancing a geolocation database (“database”) associates a user-initiated triggering event with a location in a database by sensing user position and orientation within the vehicle and a position and orientation of the vehicle. The triggering event is detected by sensors arranged within a vehicle with respect to the user. The method determines a point of interest (“POI”) near the location based on the user-initiated triggering event. The method, responsive to the user-initiated triggering event, updates the database based on information related to the user-initiated triggering event at an entry of the database associated with the POI. The database and voice assistants can leverage the enhanced data about the POI for future requests.

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: According to some aspects, a method of monitoring an acoustic environment of a mobile device, at least one computer readable medium encoded with instructions that, when executed, perform such a method and/or a mobile device configured to perform such a method is provided. The method comprises receiving acoustic input from the environment of the mobile device while the mobile device is operating in the low power mode, detecting whether the acoustic input includes a voice command based on performing a plurality of processing stages on the acoustic input, wherein at least one of the plurality of processing stages is performed while the mobile device is operating in the low power mode, and using at least one contextual cue to assist in detecting whether the acoustic input includes a voice command.

Abstract: A method includes receiving a representation of a spoken utterance, processing the representation of the spoken utterance to identify, from a number of candidate domains, a request and a serving domain, and routing the request to a personal assistant based on the request and the serving domain. Identification of the serving domain is based on one or more of a contextual state, a behavior profile of a speaker of the utterance, and a semantic content of the utterance.

Abstract: A low-complexity method and apparatus for detection of voiced speech and pitch estimation is disclosed that is capable of dealing with special constraints given by applications where low latency is required, such as in-car communication (ICC) systems. An example embodiment employs very short frames that may capture only a single excitation impulse of voiced speech in an audio signal. A distance between multiple such impulses, corresponding to a pitch period, may be determined by evaluating phase differences between low-resolution spectra of the very short frames. An example embodiment may perform pitch estimation directly in a frequency domain based on the phase differences and reduce computational complexity by obviating transformation to a time domain to perform the pitch estimation. In an event the phase differences are determined to be substantially linear, an example embodiment enhances voice quality of the voiced speech by applying speech enhancement to the audio signal.

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: A system for inputting and processing handwritten, multi-character text may comprise a handwriting recognition subsystem, a word completion subsystem, and an audio feedback system. The handwriting recognition system may be configured to capture a series of handwritten characters formed by a user and to convert the handwritten characters into a set of candidate partial text strings. The word completion subsystem may be configured to identify if a candidate partial text string constitutes a word segment and if so, generate one or both of (i) at least one clarifying word and (ii) at least one clarifying phrase that includes the clarifying word. The word segment may be an arbitrary string and not correspond to a valid complete word in a language associated with the system. The audio feedback subsystem may be configured to produce an audio representation of the word segment(s), the clarifying word(s), and the clarifying phrase(s).

Abstract: According to some aspects, a method of monitoring an acoustic environment of a mobile device, at least one computer readable medium encoded with instructions that, when executed, perform such a method and/or a mobile device configured to perform such a method is provided. The method comprises receiving acoustic input from the environment of the mobile device while the mobile device is operating in the low power mode, detecting whether the acoustic input includes a voice command based on performing a plurality of processing stages on the acoustic input, wherein at least one of the plurality of processing stages is performed while the mobile device is operating in the low power mode, and using at least one contextual cue to assist in detecting whether the acoustic input includes a voice command.

Abstract: Aspects of the disclosure are related to synthesizing speech or other audio based on input data. Additionally, aspects of the disclosure are related to using one or more recurrent neural networks. For example, a computing device may receive text input; may determine features based on the text input; may provide the features as input to an recurrent neural network; may determine embedded data from one or more activations of a hidden layer of the recurrent neural network; may determine speech data based on a speech unit search that attempts to select, from a database, speech units based on the embedded data; and may generate speech output based on the speech data.