Abstract:
One general aspect includes a vehicle including: a passenger compartment for a user; a sensor located in the passenger compartment, the sensor configured to obtain a speech request from the user; a memory configured to store a specific intent for the speech request; and a processor configured to at least facilitate: obtaining a speech request from the user; attempting to classify the specific intent for the speech request via a voice assistant; determining the voice assistant cannot classify the specific intent from the speech request; after determining the voice assistant cannot classify the specific intent, interpreting the specific intent via one or more natural language processing (NLP) methodologies; implementing the voice assistant to fulfill the speech request or accessing one or more personal assistants to fulfill the speech request or some combination thereof, after the one or more NLP methodologies has interpreted the specific intent.
Abstract:
One general aspect includes a method for detecting one or more cues in conversational speech, the method including: recognizing (via a controller) a conversation between a vehicle occupant and at least one third party; reviewing silently (via the controller) the conversation in real-time; receiving (at a controller) from the vehicle occupant or the third party a speech cue made during the conversation; in response to the received speech cue, retrieving suggestion information based on the silent review of the conversation (via the controller) from one or more suggestion databases; providing (via the controller) an audio announcement of the suggestion information configured to be announced through an audio system located in a vehicle.
Abstract:
A system and method of processing disfluent speech at an automatic speech recognition (ASR) system includes: receiving speech from a speaker via a microphone; determining the received speech includes disfluent speech; accessing a disfluent speech grammar or acoustic model in response to the determination; and processing the received speech using the disfluent speech grammar.
Abstract:
A system and method of changing features of an existing automatic speech recognition (ASR) system includes: monitoring speech received from a vehicle occupant for one or more keywords identifying a feature to remove from or add to the ASR system; detecting the keywords in the monitored speech; and adding the identified feature to or removing the identified feature from from the ASR system.
Abstract:
A vehicle including a passenger compartment having a rear seating area is described. A method for monitoring the rear seating area of the passenger compartment includes monitoring a vehicle operating state comprising one of a key-on state and a key-off state and monitoring the rear seating area. A presence or absence of a passenger in the rear seating area is detected based upon the monitoring, and a control routine is executed based upon the vehicle operating state and the presence or absence of a passenger in the rear seating area.
Abstract:
A system and method for adjusting an operating parameter of a vehicle by processing a trailer information includes a sensor and a controller. The vehicle includes a tow hitch configured to couple with a trailer. The sensor is configured to detect if the trailer is coupled to the tow hitch. The controller includes a data processing hardware and a memory hardware, the memory hardware storing instructions that when executed on the data processing hardware cause the data processing hardware to perform operations including processing the trailer information to change the vehicle operating parameter to a predetermined operating parameter if the trailer is coupled to the hitch.
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:
Methods and apparatus are provided for diagnosing a vehicle. In one embodiment, a method includes: initiating, by a processor, a recording of a noise by at least one microphone based on user selection data from a user of the vehicle; receiving, by the processor, audio signal data based on the recording; generating, by the processor, vector data based on the audio signal data; processing, by the processor, the vector data with at least one trained machine, by the processor, learning model to determine a classification of the noise; predicting, by the processor, an action to be taken based on the classification; and storing, by the processor, the audio signal data, the classification, and the action in a datastore.
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.