Abstract: A vehicle is disclosed that includes systems for adjusting the transmittance of one or more windows of the vehicle. The vehicle may include a camera outputting images taken of an occupant within the vehicle. The vehicle may also include an artificial neural network running on computer hardware carried on-board the vehicle. The artificial neural network may be trained to classify the occupant of the vehicle using the images captured by the camera as input. The vehicle may further include a controller controlling transmittance of the one or more windows based on classifications made by the artificial neural network. For example, if the artificial neural network classifies the occupant as squinting or shading his or her eyes with a hand, the controller may reduce the transmittance of a windshield, side window, or some combination thereof.

Abstract: A computing system can translate a spoken natural language command into an intermediate constructed language command with a first deep neural network and determine a vehicle command and an intermediate constructed language response with a second deep neural network based on receiving vehicle information. The computing system can translate the intermediate constructed language response into a spoken natural language response with a third deep neural network and operate a vehicle based on the vehicle command.

Abstract: A computing system can determine a vehicle command based on a received spoken language command and determined confidence levels. The computing system can operate a vehicle based on the vehicle command. The computing system can further determine the spoken language command by processing audio spectrum data corresponding to spoken natural language with an automatic speech recognition (ASR) system.

Abstract: A method for controlling an autonomous vehicle is disclosed. The method may include receiving image data. The image data may be logistically classified by a first neural network as pertaining to one situation of a plurality of situations. Based on this logistic classification, the image data may be assigned to a second neural network that is specifically trained to address the one situation. The second neural network may perform regression on the image data. Thereafter, the vehicle may be control with a command based on the regression.

Abstract: A computing system can be programmed to receive a spoken language command in response to emitting a spoken language cue and process the spoken language command with a generalized adversarial neural network (GAN) to determine a vehicle command. The computing system can be further programmed to operate a vehicle based on the vehicle command.

Abstract: A processor of a vehicle speech recognition system recognizes speech via domain-specific language and acoustic models. The processor further, in response to the acoustic model having a confidence score for recognized speech falling within a predetermined range defined relative to a confidence score for the domain-specific language model, recognizes speech via the acoustic model only.

Abstract: This disclosure generally relates to a system, apparatus, and method for achieving an adaptive vehicle state-based hands free noise reduction feature. A noise reduction tool is provided for adaptively applying a noise reduction strategy on a sound input that uses feedback speech quality measures and machine learning to develop future noise reduction strategies, where the noise reduction strategies include analyzing vehicle operational state information and external information that are predicted to contribute to cabin noise and selecting noise reducing pre-filter options based on the analysis.

Abstract: Systems, methods, and devices for speech transformation and generating synthetic speech using deep generative models are disclosed. A method of the disclosure includes receiving input audio data comprising a plurality of iterations of a speech utterance from a plurality of speakers. The method includes generating an input spectrogram based on the input audio data and transmitting the input spectrogram to a neural network configured to generate an output spectrogram. The method includes receiving the output spectrogram from the neural network and, based on the output spectrogram, generating synthetic audio data comprising the speech utterance.

Abstract: A vehicle is disclosed that uses data from different types of on-board sensors to determine whether meteorological precipitation is failing near the vehicle. The vehicle may include an on-board camera capturing image data and an on-board accelerometer capturing accelerometer data. The image data may characterize an area in front of or behind the vehicle. The accelerometer data may characterize vibrations of a windshield of the vehicle. An artificial neural network may run on computer hardware carried on-board the vehicle. The artificial neural network may be trained to classify meteorological precipitation in an environment of the vehicle using the image data and the accelerometer data as inputs. The classifications of the artificial neural network may be used to control one or more functions of the vehicle such as windshield-wiper speed, traction-control settings, or the like.

Abstract: Provided is a lab clearinghouse device configured to provide centralized management of medical tests across a plurality of medical providers, a plurality of lab payers, and a plurality of laboratories. The lab clearinghouse device is configured to communicate with a plurality of medical laboratories, medical providers, and lab payers to efficiently and effectively order and manage medical testing.

Abstract: Provided is a lab clearinghouse device configured to reduce fraud, waste, and abuse in the ordering and performance of medical testing. The lab clearinghouse device is configured to communicate with a plurality of medical laboratories, medical providers, and lab payers to efficiently and effectively reduce fraud, waste, and abuse in the ordering and performance of medical testing.

Abstract: Provided is a lab clearinghouse device configured to efficiently and effectively approve medical tests across a plurality of medical laboratories, medical providers, and lab payers. The lab clearinghouse device is configured to communicate with a plurality of medical laboratories, medical providers, and lab payers to efficiently and effectively approve, direct, and manage medical tests.

Abstract: An automatic speech recognition system for a vehicle includes a controller configured to select an acoustic model from a library of acoustic models based on ambient noise in a cabin of the vehicle and operating parameters of the vehicle. The controller is further configured to apply the selected acoustic model to noisy speech to improve recognition of the speech.

Abstract: Techniques pertaining to an autonomous police vehicle are described. A method may involve a processor associated with an autonomous vehicle obtaining an indication of violation of one or more traffic laws by a first vehicle. The method may also involve the processor maneuvering the autonomous vehicle to pursue the first vehicle. The method may further involve the processor remotely executing one or more actions with respect to the first vehicle.

Abstract: A method is disclosed for incorporating preferences of a human occupant into an autonomous driving experience. The method may include a computer system autonomously controlling speed and steering of a vehicle. While it is controlling the vehicle, the computer system may interpret a speech command received from a human occupant of the vehicle. The computer system may determine whether changing at least one of the speed and steering in accordance with the speech command would be safe and legal. If it would be safe and legal, the computer system may change the at least one of the speed and steering in accordance with the speech command. If it would not be safe and legal, the computer system may leave the at least one of the speed and steering unchanged in contravention of the speech command.

Abstract: A vehicle is disclosed that includes systems for adjusting the transmittance of one or more windows of the vehicle. The vehicle may include a camera outputting images taken of an occupant within the vehicle. The vehicle may also include an artificial neural network running on computer hardware carried on-board the vehicle. The artificial neural network may be trained to classify the occupant of the vehicle using the images captured by the camera as input. The vehicle may further include a controller controlling transmittance of the one or more windows based on classifications made by the artificial neural network. For example, if the artificial neural network classifies the occupant as squinting or shading his or her eyes with a hand, the controller may reduce the transmittance of a windshield, side window, or some combination thereof.

Abstract: A vehicle is disclosed that includes systems for adjusting the transmittance of one or more windows of the vehicle. The vehicle may include a camera outputting images taken of an occupant within the vehicle. The vehicle may also include an artificial neural network running on computer hardware carried on-board the vehicle. The artificial neural network may be trained to classify the occupant of the vehicle using the images captured by the camera as input. The vehicle may further include a controller controlling transmittance of the one or more windows based on classifications made by the artificial neural network.

Abstract: The present invention extends to methods, systems, and computer program products for detecting physical threats approaching a vehicle. External sensors on a vehicle capture the environment around the vehicle. Approaching targets detected by the external sensors can be fed into a neural network to recognize and/or classify approaching targets as potential threats. Tracking mechanisms (e.g., Kalman filters, Particle filters, etc.) can leverage temporal information to determine if a threat is approaching a vehicle. When an approaching threat is detected, a vehicle can activate one or more counter measures to deter the threat. When a vehicle includes autonomous driving capabilities, counter measures can include automatically attempting to drive away from an approaching threat.

Abstract: A method is disclosed for incorporating preferences of a human occupant into an autonomous driving experience. The method may include a computer system autonomously controlling speed and steering of a vehicle. While it is controlling the vehicle, the computer system may interpret a speech command received from a human occupant of the vehicle. The computer system may determine whether changing at least one of the speed and steering in accordance with the speech command would be safe and legal. If it would be safe and legal, the computer system may change the at least one of the speed and steering in accordance with the speech command. If it would not be safe and legal, the computer system may leave the at least one of the speed and steering unchanged in contravention of the speech command.

Abstract: A system includes a head and torso simulation (HATS) system configured to play back pre-recorded audio commands while simulating a driver head location as an output location. The system also includes a vehicle speaker system and a processor configured to engage a vehicle heating, ventilation and air-conditioning (HVAC) system. The processor is also configured to play back audio commands through the HATS system while playing back pre-recorded vehicle environment noises through the speaker system. The processor is further configured to determine if the audio command, recorded by a vehicle microphone, is recognizable in the presence of the environment noises and HVAC noises. Also, the processor is configured to repeat the engagement, playback of commands and noises, and determination, recording the results of the determination for each command in a set of commands.