Abstract: The concepts include a user support system in the form of a microphone, a visual display arranged in a vehicle cabin, and a controller. The controller includes an instruction set that is executable to receive, via the microphone, a voice-based request from a user, and employ a virtual assistant to determine a user interaction in real time and to determine a specific intent for the voice-based request, including capturing metadata. A user interaction routine determines a user interaction parameter associated with the virtual assistant based upon the voice-based request from the user. A user sentiment analysis routine determines a user satisfaction parameter associated with the virtual assistant based upon the voice-based request from the user. The controller responds in real-time to the voice-based request based upon the user satisfaction parameter and the user interaction parameter that are associated with the virtual assistant.

Abstract: An automatic rain response system includes microphones of a vehicle, windshield wipers, and a controller. The microphones generate acoustic signals in response to rain. The controller is configured to receive a local weather condition, extract acoustic features from the acoustic signals, form feature vectors in response to the acoustic features and the local weather condition, classify the feature vectors to determine a current class among multiple classes, activate the windshield the wipers at a high speed in response to the current class being a heavy rain on a windshield class, activate the windshield wipers at a medium speed in response to the current class being a freezing rain on the windshield class, activate the windshield wipers at a low speed in response to the current class being a light rain on the windshield class, and deactivate the windshield wipers in response to the current class being a no rain class.

Abstract: A system for scenario context-aware voice assistant auto-activation is provided. The system includes a microphone configured for providing data related to a word or a phrase spoken by a user, an operational device, and a computerized scenario context-aware voice assistant controller. The controller includes programming to recognize the word or the phrase within the data and identify a scenario context of the word or the phrase. The controller further includes programming to utilize the scenario context to associate the word or the phrase with a scenario context feature trigger configured for indicating a desired command of the user and command the operational device based upon the scenario context feature trigger associated with the word or the phrase.

Abstract: A method and associated system for recognizing speech using multiple speech recognition algorithms. The method includes receiving speech at a microphone installed in a vehicle, and determining results for the speech using a first algorithm, e.g., embedded locally at the vehicle. Speech results may also be received at the vehicle for the speech determined using a second algorithm, e.g., as determined by a remote facility. The results for both may include a determined speech topic and a determined speech slotted value, along with corresponding confidence levels for each. The method may further include using at least one of the determined first speech topic and the received second speech topic to determine the topic associated with the received speech, even when the first speech topic confidence level of the first speech topic, and the second speech topic confidence level of the second speech topic are both a low confidence level.

Abstract: A system and method of automated speech recognition using a dynamically-adjustable listening timeout. The method includes: receiving speech signals representing a first speech segment during a first speech listening period; during the first speech listening period, processing the received speech signals representing the first speech segment to determine whether the first speech segment includes one or more insignificant utterances; adjusting a listening timeout in response to the determination of whether the first speech segment includes one or more insignificant utterances; listening for subsequent received speech using the adjusted listening timeout; and performing automatic speech recognition on the received speech signals and/or the subsequently received speech signals.

Abstract: A system and method of automated speech recognition using a dynamically-adjustable listening timeout. The method includes: receiving speech signals representing a first speech segment during a first speech listening period; during the first speech listening period, processing the received speech signals representing the first speech segment to determine whether the first speech segment includes one or more insignificant utterances; adjusting a listening timeout in response to the determination of whether the first speech segment includes one or more insignificant utterances; listening for subsequent received speech using the adjusted listening timeout; and performing automatic speech recognition on the received speech signals and/or the subsequently received speech signals.

Abstract: A method and associated system for recognizing speech using multiple speech recognition algorithms. The method includes receiving speech at a microphone installed in a vehicle, and determining results for the speech using a first algorithm, e.g., embedded locally at the vehicle. Speech results may also be received at the vehicle for the speech determined using a second algorithm, e.g., as determined by a remote facility. The results for both may include a determined speech topic and a determined speech slotted value, along with corresponding confidence levels for each. The method may further include using at least one of the determined first speech topic and the received second speech topic to determine the topic associated with the received speech, even when the first speech topic confidence level of the first speech topic, and the second speech topic confidence level of the second speech topic are both a low confidence level.

Abstract: A processor receives a broadcast in a vehicle, select audio data from the broadcast, processes the audio data selected from the broadcast, determines a phonetic pattern of the selected audio data based on the processing, selects additional instances of audio data from the broadcast that resemble the selected audio data, processes the additional instances of audio data from the broadcast, determine phonetic patterns of the additional instances of audio data, and selects a plurality of phonetic patterns from the phonetic pattern of the selected audio data and the phonetic patterns of the additional instances of audio data. A transmitter transmits the plurality of phonetic patterns to a server to determine an optimal pronunciation of the selected audio data based on a statistical analysis of the plurality of phonetic patterns and to add the optimal pronunciation of the selected audio data to a database used to recognize speech in the vehicle.

Abstract: A processor receives a broadcast in a vehicle, select audio data from the broadcast, processes the audio data selected from the broadcast, determines a phonetic pattern of the selected audio data based on the processing, selects additional instances of audio data from the broadcast that resemble the selected audio data, processes the additional instances of audio data from the broadcast, determine phonetic patterns of the additional instances of audio data, and selects a plurality of phonetic patterns from the phonetic pattern of the selected audio data and the phonetic patterns of the additional instances of audio data. A transmitter transmits the plurality of phonetic patterns to a server to determine an optimal pronunciation of the selected audio data based on a statistical analysis of the plurality of phonetic patterns and to add the optimal pronunciation of the selected audio data to a database used to recognize speech in the vehicle.