An aspect of the invention is directed to a system of both atmospheric and underwater sensors for measuring pressure waves from a noise source. A system of pressure sensors can be formed to determine the location of an external noise source, whether in air or underwater. The system includes at least two arrays consisting of pressure sensors, including at least one atmospheric pressure sensor and at least one underwater pressure sensor, such as a hydrophone. Each sensor may be a seven-fiber intensity modulated fiber optic pressure sensor. The system includes an analog to digital converter for digitizing the pressure data received from each sensor and a processor which processes the received signals to calculate an approximate location of the noise source based upon the pressure signals received by the sensors at different times of arrival. The system can provide this capability in remote applications due to its low power requirements.

A system for monitoring an acoustic scene outside a vehicle; the system including: a vehicle with wheels and a trunk, an acoustic sensor disposed in the trunk, a control unit operatively connected to the acoustic sensor, and at least one neural network operatively connected to the control unit, and trained in such a way to correlate the characteristics of an audio signal with types of road surfaces; the control unit is configured in such a way to receive an audio signal detected by the acoustic sensor while the vehicle is traveling, extract the characteristics of the audio signal and input said characteristics of the audio signal to the neural network in order to identify the type of road surface covered by the vehicle wheels.

A system for monitoring an acoustic scene outside a vehicle; the system including: a vehicle with wheels and a trunk, an acoustic sensor disposed in the trunk, a control unit operatively connected to the acoustic sensor, and at least one neural network operatively connected to the control unit, and trained in such a way to correlate the characteristics of an audio signal with types of road surfaces; the control unit is configured in such a way to receive an audio signal detected by the acoustic sensor while the vehicle is traveling, extract the characteristics of the audio signal and input said characteristics of the audio signal to the neural network in order to identify the type of road surface covered by the vehicle wheels.

A directional receiver system may include a receiver, a plurality of receive antenna elements, and a circuit. The receiver may include an input port and an output. The plurality of receive antenna elements may be fixedly configured into a known geometric relationship to each other, and each of the receive antenna elements may be connected to the input port of the receiver. The circuit may be coupled to the output of the receiver, configured to determine time differences at which signals from a source are incident upon the antenna elements, and configured to determine an angular orientation of the source to the receive antenna elements based on the time differences.

The reliable differentiation of human and artificial talkers is important for many automatic speaker verification applications, such as in developing anti-spoofing countermeasures against replay attacks for voice biometric authentication. A multi-microphone approach may exploit small movements of human talkers to differentiate between a human talker and an artificial talker. One method of determining the presence or absence of talker movement includes monitoring the variation of the inter-mic frequency-dependent phase profile of the received microphone array data over a period of time. Using spatial information with spectral-based techniques for determining whether an audio source is a human or artificial talker may reduce the likelihood of success of spoofing attacks against a voice biometric authentication system. The anti-spoofing countermeasure may be used in electronic devices including smart home devices, cellular phones, tablets, and personal computers.

A vehicle driving control apparatus includes a communication interface configured to receive, from a sound sensor, a signal corresponding to sound that is generated in an external environment, and a processor configured to identify a sound object generating the sound, by obtaining a type of the sound object and either one or both of a direction of the sound object and a distance from the sound object to a vehicle including the vehicle driving control apparatus, based on the received signal, and control driving of the vehicle, based on the identified sound object.

Systems and methods are disclosed for autonomous joint detection-classification of acoustic sources of interest. Localization and tracking from unmanned marine vehicles are also described. Based on receiving acoustic signals originating above or below the surface, a processor can process the acoustic signals to determine the target of interest associated with the acoustic signal. The methods and systems autonomously and jointly detect and classify a target of interest. A target track can be generated corresponding to the locations of the detected target of interest. A classifier can be used representing spectral characteristics of a target of interest.

Provided is an electronic apparatus. The electronic apparatus includes an audio receiver configured to obtain an audio signal of sound output by an external object; a sensor configured to sense a posture of the electronic apparatus; a display; and a processor configured to, based on the audio signal that is obtained by the audio receiver, determine a direction in which the external object is located with respect to the electronic apparatus, and control the display to display a graphical object that corresponds to the external object based on the posture of the electronic apparatus sensed by the sensor and the direction in which the external object is located.

Provided is an electronic apparatus. The electronic apparatus includes an audio receiver configured to obtain an audio signal of sound output by an external object; a sensor configured to sense a posture of the electronic apparatus; a display; and a processor configured to, based on the audio signal that is obtained by the audio receiver, determine a direction in which the external object is located with respect to the electronic apparatus, and control the display to display a graphical object that corresponds to the external object based on the posture of the electronic apparatus sensed by the sensor and the direction in which the external object is located.

Methods and systems for spatial filtering transmitters and receivers capable of simultaneous communication with one or more receivers and transmitters, respectively, the receivers capable of outputting source directions to humans or devices. The methods and systems use spherical wave field partial wave expansion (PWE) models for transmitted and received fields at antennas and for waves generated by contributing sources. The source PWE models have expansion coefficients expressed as functions of directional coordinates of the sources. For spatial filtering receivers a processor uses the output signals from at least one sensor outputting signals consistent with Nyquist criteria representative of the wave field and the source PWE model to determines directional coordinates of sources (wherein the number of floating point operations are reduced) and outputs the directional coordinates and communications to a reporter configured for reporting information to humans. For spatial filtering transmitters a processor uses known receiver directions and source partial wave expansions to generate signals for transducers producing a composite total wave field conveying communications to the specified receivers. The methods and communications reduce the processing required for transmitting and receiving spatially filtered communcations.