Abstract: A communication augmentation system includes a camera, a transceiver and a computer. The camera is operation to record an image of users. The transceiver is operational to receive inbound messages from wireless devices. The inbound messages include an input content. The computer is operational to store registrations of the users, determine user locations where the users are located in response to facial profiles relative to the image, determine device locations where the wireless devices are located based on the inbound messages, associate the wireless devices with the users based on the user locations and the device locations, determine destinations of the inbound messages based on a comparison of input content to the identifiers, and transfer the input content and the destinations to the transceiver. The transceiver is further operational to transmit the input content in a plurality of outbound messages to the wireless devices based on the destinations.

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: A method for determining a sampling rate of occupancy data for a vehicle includes determining a vehicle speed and detecting whether an interrupt condition is present. If the speed is within a first speed range and no interrupt condition is detected, then a first sampling rate is selected for sampling the occupancy data. If the speed is within a second speed range that is higher than the first speed range, and/or if the interrupt condition is detected, then a second sampling rate which is faster than the first sampling rate is selected for sampling the occupancy data. A primary electronic control unit (ECU) may be configured for sampling the occupancy data. If the second sampling rate is selected and a computational demand of the primary ECU exceeds a predetermined threshold, then a portion of the computational demand may be transferred to one or more secondary ECUs for sampling the data.

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 creating vehicle lighting atmosphere of a vehicle is provided. The system includes ambient lighting including a plurality of lights configured for illuminating an interior of the vehicle or an exterior of the vehicle with a selectable light color. The system further includes a computerized vehicle lighting controller, including programming to monitor an input useful to select an ambient lighting theme, select an ambient lighting theme based upon the input, and generate a command to control the ambient lighting based upon the ambient lighting theme.

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: 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 includes virtually dividing a cargo area of a vehicle into a plurality of virtual cells. The method also includes creating, by implementing machine learning, a load profile for the cargo area. The load profile indicates a weight estimate at each of the plurality of virtual cells based on a load in the cargo area. Guidance on moving the load within the cargo area is provided based on the load profile to balance the load in the cargo area.

Abstract: A motor vehicle includes a body defining a passenger compartment and having opposing driver and passenger sides. The vehicle includes driver and passenger side mirrors. The driver side mirror has a sweep angle (?) and an elevation angle (?). The passenger side mirror has a sweep angle (?). The side mirrors are separated from each other by a distance (D). An adjustable driver seat has a height (H). An electronic controller, in response to position signals inclusive of angles (?), (?), and (?), the distance (D), and the height (H), calculates a three-dimensional (3D) driver head position of a driver of the vehicle, and thereafter uses the 3D driver head position to improve performance of a driver assist system device. Functions of the controller may be implemented as a method or recorded on a computer readable medium for execution by a processor.

Abstract: A vehicle includes a plurality of microphones to obtain speech from a person outside the vehicle as an input signal and a sensor system to determine a location and orientation of the person relative to the vehicle. The vehicle also includes a controller to determine characteristics of the input signal and to determine whether to perform speech enhancement on the input signal based on one or more of the characteristics and the location and orientation of the person.

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 for text feedback includes: receiving, by a controller, an utterance from a user; determining, by an automatic speech recognition engine of the controller, a plurality of speech recognition results based on the utterance from the user, wherein the speech recognition results include probable commands; determining, by the automatic speech recognition engine of the controller, a plurality of confidence scores for each of the plurality of speech recognition results; determining, by the controller, a text characteristic for each of the plurality of probable commands as a function of the confidence scores for each of the plurality of speech recognition results; and commanding, by the controller, a display to show text corresponding to each of the plurality of probable commands with the text characteristic determined by the controller.

Abstract: A vehicle includes a plurality of microphones to obtain speech from a person outside the vehicle as an input signal and a sensor system to determine a location and orientation of the person relative to the vehicle. The vehicle also includes a controller to determine characteristics of the input signal and to determine whether to perform speech enhancement on the input signal based on one or more of the characteristics and the location and orientation of the person.

Abstract: A method to operate a virtual assistant for a motor vehicle includes one or more of the following: determining if the virtual assistant is dormant; activating the virtual assistant if dormant; and accomplishing an action by the virtual assistant.

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: 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: 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 generating a natural language generation (NLG) output, wherein the method includes: receiving speech signals from a user at a microphone of a client device; determining a requested communication goal and at least one inputted communication value based on the received speech signals; determining to use a static natural language generation (NLG) template or a dynamic NLG template to generate an NLG output, wherein the determination of whether to use a static NLG template or a dynamic NLG template is made using a neural network NLG template selection process; selecting an NLG template after the determination of whether to use a static NLG template or a dynamic NLG template; and generating an NLG output based on the selected NLG template.