Embodiments of the present disclosure a computer-implemented method comprising receiving sensor data from one or more vibration sensors that are embedded within a seat, where the sensor data includes data associated with speech by an occupant of the seat, and at least one of processing, transmitting, or storing the sensor data based on the data associated with the speech.

An audio control system for a vehicle includes a processor, a non-volatile memory module having stored therein instructions for controlling one or more vehicle audio components, a sensor operable to detect a change in vehicle configuration, and a control module operable to adjust a vehicle audio component based on the change in vehicle configuration according to instructions stored in the non-volatile memory module.

An electronic device includes one or more microphones that generate audio signals and a wind noise detection subsystem. The electronic device may also include a wind noise reduction subsystem. The wind noise detection subsystem applies multiple wind noise detection techniques to the set of audio signals to generate corresponding indications of whether wind noise is present. The wind noise detection subsystem determines whether wind noise is present based on the indications generated by each detection technique and generates an overall indication of whether wind noise is present. The wind noise reduction subsystem applies one or more wind noise reduction techniques to the audio signal if wind noise is detected. The wind noise detection and reduction techniques may work in multiple domains (e.g., the time, spatial, and frequency domains).

Techniques are provided for audio-based detection and tracking of an acoustic source. A methodology implementing the techniques according to an embodiment includes generating acoustic signal spectra from signals provided by a microphone array, and performing beamforming on the acoustic signal spectra to generate beam signal spectra, using time-frequency masks to reduce noise. The method also includes detecting, by a deep neural network (DNN) classifier, an acoustic event, associated with the acoustic source, in the beam signal spectra. The DNN is trained on acoustic features associated with the acoustic event. The method further includes performing pattern extraction, in response to the detection, to identify time-frequency bins of the acoustic signal spectra that are associated with the acoustic event, and estimating a motion direction of the source relative to the array of microphones based on Doppler frequency shift of the acoustic event calculated from the time-frequency bins of the extracted pattern.

A system for haptic stimulation includes: an actuation subsystem having a set of actuators, a support subsystem, a rigid housing, a sensor subsystem, a control module, and an electrical subsystem. A method for manufacturing a system for haptic stimulation includes performing a set of injection molding processes to form the support subsystem and/or the rigid housing; integrating the actuation subsystem within the support subsystem; and coupling the rigid housing to the support subsystem.

A hearing protection device is presented. The hearing protection device includes a first and second earmuffs (202, 260, 310) connected by a connector (270, 320). The first and second earmuffs are configured to provide level dependent hearing protection. The first earmuff includes a microphone element (204, 330) having a microphone entry (264), positioned on an exterior of a housing of the first earmuff (260), the microphone element (204, 330) being configured to receive an ambient sound. The first earmuff also includes a processor configured to process the ambient sound using a level dependent function. The first earmuff also includes a speaker configured to broadcast the processed ambient sound in an interior of the first earmuff. The first earmuff also includes an asymmetrical windscreen (262) configured to enclose the microphone element. The windscreen is coupled to the housing of the first earmuff.

A system and method can provide nose, such as wind noise, mitigation and/or microphone blending. Some methods may include sampling a sound signal from a plurality of microphones to generate a frame comprising a plurality of time-frequency tiles of the sound signal, each time-frequency tile including respective values of at least one feature from the plurality of microphones, comparing the respective values of the at least one feature to determine whether each time-frequency tile satisfies a similarity threshold, and flagging each time-frequency tile as noise if it fails to satisfy the similarity threshold, grouping the plurality of time-frequency tiles into sets of frequency-adjacent time-frequency tiles, and for each set of frequency-adjacent time-frequency tiles in the frame: counting a number of flagged time-frequency tiles, and attenuating all of the time-frequency tiles in the each set if the number exceeds a noise bin count threshold to thereby reduce noise in the sound signal.

A system includes a microphone unit coupled to a roof of an autonomous vehicle. The microphone unit includes a microphone board having a first opening. The microphone unit also includes a first microphone positioned over the first opening and coupled to the microphone board. The microphone unit further includes an accelerometer. The system also includes a processor coupled to the microphone unit.

An apparatus and method for monitoring audio output is disclosed. The apparatus may comprise means for providing one or more primary audio signals based on signals from one or more first microphones associated with an audio capture device and providing one or more secondary audio signals based on signals from one or more second microphones associated with an audio monitoring device, the audio monitoring device being separate from the audio capture device and configured for output of the one or more primary audio signals and the one or more secondary audio signals through one or more loudspeakers. The apparatus may comprise means for modifying one or both of the primary and secondary audio signals such that output of the one or more primary audio signals are distinguished over output of the one or more secondary audio signals.

Methods, systems, computer-readable media, devices, and apparatuses for synchronized mode transitions are presented. A first device configured to be worn at an ear includes a processor configured to, in a first contextual mode, produce an audio signal based on audio data. The processor is also configured to, in the first contextual mode, exchange a time indication of a first time with a second device. The time indication is exchanged based on detection of a first condition of a microphone signal. The processor is further configured to, at the first time, transition from the first contextual mode to a second contextual mode based on the time indication.