An image capture device includes a housing that includes a pattern of apertures and a microphone disposed within the housing and proximate to the apertures. The image capture device includes a membrane assembly. The membrane assembly includes a support disposed between the housing and the microphone and a channel defined in the support that directs sound waves from only one of the apertures in the pattern to the microphone. The membrane assembly further includes a membrane that extends across the channel and separates the one of the apertures and the microphone.

A vehicle device may receive audio data and other vehicle data associated with a vehicle and may transform the audio data to transformed audio data in a frequency domain. The vehicle device may segment the transformed audio data into a plurality of audio segments and may process the plurality of audio segments, with different feature extraction techniques, to extract a plurality of feature vectors. The vehicle device may merge the plurality of feature vectors into a merged feature vector and may create an audio signature for the audio data based on the merged feature vector. The vehicle device may process the audio signature and the other vehicle data, with a model, to determine a classification of the audio signature and may perform one or more actions based on the classification of the audio signature.

Illustrative embodiments enable a MEMS transducer to quickly recover from, acoustic overload events by quickly resetting signal processing circuitry downstream from a MEMS transducer. An acoustic overload sensor detects occurrence of an acoustic overload event, and triggers a reset circuit to operate a set of switches to rapidly drain charge from a corresponding set of capacitances within the transducer, or within the signal processing circuitry, thereby resetting the signal processing circuitry more rapidly than would occur if said transducer or circuitry were allowed to recover on its own.

Disclosed herein is an intelligent robot cleaner. The intelligent robot cleaner primarily senses foreign matter sucked through a suction unit under the control of a control unit, and secondarily senses an article collected in a collection unit, if articles other than the foreign matter are sensed, thus allowing a use to recognize accurate information about the article collected in the collection unit and preventing valuables or small articles from being lost. The intelligent robot device may be associated with an artificial intelligence module, a unmanned aerial vehicle (UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, devices related to 5G services, and the like.

A method of making a piezoelectric sensor includes forming piezoelectric layer(s) to define a beam extending between a proximal portion and a distal end. The method also includes modeling a strain distribution on the beam based on a force applied to the beam, and defining an outer boundary with a shape substantially corresponding to a contour line of the strain distribution on the beam. The method also includes forming an electrode having said outer boundary shape, and attaching the electrode to the beam. The method also includes attaching the beam to a substrate in cantilever form so that the proximal portion of the beam is anchored to the substrate and the distal end of the beam is unsupported.

A vehicle device may receive audio data and other vehicle data associated with a vehicle and may transform the audio data to transformed audio data in a frequency domain. The vehicle device may segment the transformed audio data into a plurality of audio segments and may process the plurality of audio segments, with different feature extraction techniques, to extract a plurality of feature vectors. The vehicle device may merge the plurality of feature vectors into a merged feature vector and may create an audio signature for the audio data based on the merged feature vector. The vehicle device may process the audio signature and the other vehicle data, with a model, to determine a classification of the audio signature and may perform one or more actions based on the classification of the audio signature.

A noise monitoring device and a method of monitoring a location are disclosed. In one example, the noise monitoring device includes: (1) a microphone configured to detect noise proximate the noise monitoring device and derive raw data therefrom, and (2) a processor configured to determine when at least a portion of the raw data exceeds a threshold during a time period. In one example, the method of monitoring a location includes: (1) deriving raw data from noise proximate a noise monitoring device at the location, (2) comparing, for a designated period of time, at least a portion of the raw data to a threshold, and (3) determining an occurrence of an event at the location based on the comparing.

An electronic device localizes an audio source by normalizing an amplitude of an audio signal over a time period. The electronic device receives, from one or more microphones of the electronic device, signal(s) representative of audio emitted by an audio source over a time period. The electronic device estimates amplitudes of the signal(s) at a first time within the time period and at a second time within the time period, where the second time is different from the first time. The electronic device normalizes the amplitudes associated with the first and second times to generate normalized amplitudes. The electronic device determines a combined amplitude representative of the audio emitted by the audio source by combining the normalized amplitudes. The electronic device determines, based at least in part on the combined amplitude and motion of the electronic device, an estimated position of the audio source relative to the electronic device.

According to an embodiment, a circuit includes a high-Ω resistor including a plurality of semiconductor junction devices coupled in series and a plurality of additional capacitances formed in parallel with the plurality of semiconductor junction devices. Each semiconductor junction device of the plurality of semiconductor junction devices includes a parasitic doped well capacitance configured to insert a parasitic zero in a noise transfer function of the high-Ω resistor. Each additional capacitance of the plurality of additional capacitances is configured to adjust a parasitic pole in the noise transfer function of the high-Ω resistor in order to compensate for the parasitic zero.

An electronic device localizes an audio source by normalizing an amplitude of an audio signal over a time period. The electronic device receives, from one or more microphones of the electronic device, signal(s) representative of audio emitted by an audio source over a time period. The electronic device estimates amplitudes of the signal(s) at a first time within the time period and at a second time within the time period, where the second time is different from the first time. The electronic device normalizes the amplitudes associated with the first and second times to generate normalized amplitudes. The electronic device determines a combined amplitude representative of the audio emitted by the audio source by combining the normalized amplitudes. The electronic device determines, based at least in part on the combined amplitude and motion of the electronic device, an estimated position of the audio source relative to the electronic device.