Abstract: A system configured to improve sound source localization (SSL) processing by reducing a number of direction vectors and grouping the direction vectors into direction cells is provided. The system performs clustering to generate a smaller set of direction vectors included in a delay-direction codebook, reducing a size of the codebook to the number of unique delay vectors. In addition, the system groups the direction vectors into direction cells having a regular structure (e.g., predetermined uniformity and/or symmetry), which simplifies SSL processing and results in a substantial reduction in computational cost. The system may also select between multiple codebooks and/or dynamically adjust the codebook to compensate for changes to the microphone array. For example, a device with a microphone array fixed to a display that can tilt may adjust the codebook based on a tilt angle of the display to improve accuracy.

Abstract: A system includes a memory and a processor. The memory is configured to store a machine learning (ML) model. The processor is configured to (i) obtain a set of training audio signals that are labeled with respective levels of distortion, (ii) convert the training audio signals into respective images, (iii) train the ML model to estimate the levels of the distortion based on the images, (iv) receive an input audio signal, (v) convert the input audio signal into an image, and (vi) estimate a level of the distortion in the input audio signal, by applying the trained ML model to the image.

Abstract: An electronic device comprising circuitry configured to perform (402; 702; 1204) source separation (201) based on a received audio input to obtain a separated source, to perform onset detection (202) on the separated source to obtain an onset detection signal and to mix (405; 706; 1207) the audio signal with the separated source based on the onset detection signal to obtain an enhanced separated source.

Abstract: A device that includes an adaptive acoustic detection circuit and an acoustic sensor device such as a microphone is described. The device includes in addition to the sensor a circuit configured to detect when an input stimulus to the sensor satisfies an adaptive threshold, and further configured to produce a signal upon detection that causes adjustment of performance of the device, wherein the adaptive threshold is a threshold value that varies over time in accordance with detected changes to sound of an environment in which the device is located.

Abstract: Methods and apparatus for pre-scaling media content to facilitate audience measurement are disclosed. An example method includes encoding a media content sample in accordance with a first encoding configuration and playing the encoded sample. The example method also includes attempting to detect the codes in the sample, and computing a ratio between the codes encoded in the sample and the codes detected when the sample is played.

Abstract: In certain aspects, a noise suppression method and system for a personal sound amplification product (PSAP) are disclosed. An environmental audio signal acquired through one or more microphones is processed to generate a set of first sub-band signals in a set of first sub-bands. The environmental audio signal is also processed to generate a set of second sub-band signals in a set of second sub-bands. A set of first gains for the set of first sub-band signals in the set of first sub-bands is determined based on the set of second sub-band signals in the set of second sub-bands. The set of first sub-band signals is processed based on the set of first gains to generate a noise-suppressed audio signal.

Abstract: Disclosed embodiments may relate to systems and methods for monitoring and/or mapping noise data from a plurality of noise monitoring devices. In some embodiments, the plurality of noise monitoring devices may include hearing protection devices configured to detect noise, and typically may communicate such noise data (which may also include location) so that the noise data can be pooled. The pooled noise data from the plurality of noise monitoring devices may then be used to the benefit of one or more of such noise monitoring devices.

Abstract: A system including an audio source device having a first microphone and a first speaker for directing sound into an environment in which the audio source device is located and a wireless audio receiver device having a second microphone and a second speaker for directing sound into a user's ear. The audio source device is configured to 1) capture, using the firs microphone, speech of the user as a first audio signal, 2) reduce noise in the first audio signal to produce a speech signal, and 3) drive the first speaker with the speech signal. The wireless audio receiver device is configured to 1) capture, using the second microphone, a reproduction of the speech produced by the first speaker as a second audio signal and 2) drive the second speaker with the second audio signal to output the reproduction of the speech.

Abstract: A computer-implemented method, computer program product, and computing system is provided for determining quality of experience for communication sessions. In an implementation, a method may include determining a plurality of intrusive quality of experience scores associated with a plurality of intrusive audio transmission samples. The method may also include determining a plurality of non-intrusive quality of experience scores associated with a plurality of non-intrusive audio transmission samples. The method may further include deriving a quality of experience coefficient based upon a relationship between the plurality of intrusive quality of experience scores and the plurality of non-intrusive quality of experience scores.

Abstract: Example embodiments relate to vehicle sensor modules with external audio receivers. An example sensor module may include sensors and can be coupled to a vehicle's roof with a first microphone positioned proximate to the front of the sensor module. The sensor module can also include a second microphone extending into a first side of the sensor module such that the second microphone is configured to detect audio originating from an environment located relative to a first side of the vehicle and a third microphone extending into a second side of the sensor module such that the third microphone is configured to detect audio originating from the environment located relative to a second side of the vehicle, wherein the second side is opposite of the first side.

Abstract: Techniques are described for delivery and handling of automated user-responsive video sub-content. For example, a user is consuming video content associated with content-of-interest (COI) identifiers corresponding to certain sub-content relevant to the video content during certain playback time windows. During playback, embodiments use one or more sensors detect dynamic user input. At some time during playback of the video content, some of the COI identifiers are considered to be actively relevant, and detected dynamic user input is determined to invoke at least one of the actively relevant COI identifiers. A COI query can automatically be generated based on the invoked one or more COI identifiers, and a corresponding query response can be automatically generated and output to the user based on response data associated with the invoked one or more COI identifiers.

Abstract: A system includes multiple microphone arrays positioned at different locations on a roof of an autonomous vehicle. Each microphone array includes two or more microphones. Internal clocks of each microphone array are synchronized by a processor and used to generate timestamps indicating when microphones capture a sound. Based on the timestamps, the processor is configured to localize a source of the sound.

Abstract: This application discloses a sound acquisition component array, including: two first sound acquisition components, two second sound acquisition components, and two third sound acquisition components. The two second sound acquisition components are located at a first side of a line connecting the two first sound acquisition components, and the two third sound acquisition components are located at a second side of the connecting line that is opposite to the first side of the connecting line; the two second sound acquisition components are symmetrical about a perpendicular bisector of the connecting line, and the two third sound acquisition components are symmetrical about the perpendicular bisector; and a distance between the two first sound acquisition components, a distance between the two second sound acquisition components, and a distance between the two third sound acquisition components are respectively different from one another along a direction defined by the connecting line.

Abstract: Systems and methods are described to extract desired audio from an apparatus to be worn on a user's wrist. The apparatus includes a wrist wearable device, configured to be worn on the user's wrist. The wrist wearable device includes a first microphone. The first microphone has a first response pattern. The first microphone is coupled to the wrist wearable device. The first microphone is positioned on the wrist wearable device to receive a voice signal from a user when the wrist wearable device is on the user's wrist.

Abstract: The present invention relates to circuitry comprising: interpolation filter circuitry configured to receive a digital input signal and to output an interpolated digital signal; amplifier circuitry configured to generate an output signal based on the interpolated digital signal; and protection circuitry. The protection circuitry is configured to activate in response to detection of a fault condition at an output of the amplifier circuitry. The circuitry further comprises first detection circuitry configured to output a control signal to disable the protection circuitry on detection of a transient signal at an output of the interpolation filter circuitry that is unrelated to a fault.

Abstract: An acoustic garbage classification method using a one-dimensional convolutional neural network (1D-CNN) is provided. The method includes: acquiring sound signals generated by falling garbage; preprocessing the sound signals; acquiring and preprocessing the sound signals of different types of garbage, building a sound database for garbage classification, and establishing and training a 1D-CNN model; acquiring a sound signal of garbage to be classified, and inputting the sound signal into the trained 1D-CNN for garbage classification to obtain a classification result. The present disclosure is helpful to assist people in accurate garbage classification, improves the accuracy of garbage classification and recycling, and has high practical and popularization value.

Abstract: Introduced here are computer programs and associated computer-implemented techniques for deriving insights into the health of patients through analysis of audio data generated by electronic stethoscope systems. A diagnostic platform may be responsible for examining the audio data generated by an electronic stethoscope system so as to gain insights into the health of a patient. The diagnostic platform may employ heuristics, algorithms, or models that rely on machine learning or artificial intelligence to perform auscultation in a manner that significantly outperforms traditional approaches that rely on visual analysis by a healthcare professional.

Abstract: One example method includes performing sound quality operations. Microphone arrays are used to cancel or reduce or suppress background noise and to enhance speech. Subjective user input is received by an orchestration engine. The orchestration engine generates an output that includes at least adjustments to a microphone array. Controlling the microphone array based, in part, on subjective user feedback, allows desired speech or desired sound to be heard more clearly by the user.

Abstract: A collaborative distributed microphone array is configured to perform or be used in sound quality operations. A distributed microphone array can be operated to provide sound quality operations including sound suppression operations and speech intelligibility operations for multiple users in the same environment.

Abstract: An example process includes receiving a voltage input and a current input associated with one or more audio signals, bandpass filtering the voltage input and the current input, determining a root means square of the bandpass filtered portion, dividing the determined root means square of the voltage by the root means square of the current to identify an impedance value, and determining whether a fault has occurred based on the impedance value.

Abstract: In an embodiment, a method comprises: capturing, by one or more microphone arrays of a vehicle, sound signals in an environment; extracting frequency spectrum features from the sound signals; predicting, using an acoustic scene classifier and the frequency spectrum features, one or more siren signal classifications; converting the one or more siren signal classifications into one or more siren signal event detections; computing time delay of arrival estimates for the one or more detected siren signals; estimating one or more bearing angles to one or more sources of the one or more detected siren signals using the time delay of arrival estimates and a known geometry of the microphone array; and tracking, using a Bayesian filter, the one or more bearing angles. If a siren is detected, actions are performed by the vehicle depending on the location of the emergency vehicle and whether the emergency vehicle is active or inactive.

Abstract: This is directed to controlling the output of audio based on the mode of an electronic device. In particular, this is directed to an electronic device having a sound mode, silent mode, and mute mode controlling the output of audio along different audio output routes. In the sound mode, all audio can be output, while only registered or authorized audio can be output in the silent mode. In the mute mode, no audio can be output. The sound and silent modes can be enabled using an interface of the device (e.g., a switch having two possible states), while the mute mode can be enabled using an accessory coupled to the device. To disengage the mute mode, a user can provide a corresponding instruction using the accessory, or providing an instruction on the device related to volume control. For example, a user can change the device volume using an on-device interface, or toggle a sound/silent switch to a sound mode.

Abstract: Embodiments described herein involve an auxiliary zone contributing audio to a primary zone. In an example implementation, a network media system determines that a first zone in the network media system is playing back a first type of audio content and that a second zone in the network media system is not playing back audio content. While the first zone is playing back the first type of audio content and the second zone is not playing back audio content, the network media system forms a temporarily playback configuration. In the temporary playback configuration, the first zone plays back primary audio content including full frequency range audio content and the second playback device of the second zone plays back auxiliary audio content including low frequency range audio content.

Abstract: The sound signal processing method includes obtaining a sound signal of a sound source, convolving, according to a location of the sound source an impulse response of an early reflection sound with the sound signal to generate an early reflection sound control signal that reproduces an early reflection sound, and convolving an impulse response of a reverberant sound with the sound signal to generate a reverberant sound control signal that reproduces a reverberant sound.

Abstract: A system configured to perform directional speech separation. The system may dynamically associate direction-of-arrivals with one or more audio sources in order to generate output audio data that separates each of the audio sources. The system identifies a target direction for each audio source, dynamically determines directions that are correlated with the target direction, and generates output signals for each audio source. The system may associate individual frequency bands with specific directions based on a time delay detected by two or more microphones. The system may determine a cross-correlation between each direction and the target direction and select directions with strong correlation. The system may generate time-frequency mask data indicating frequency bands corresponding to the directions associated with a particular audio source. Using the mask data, the system generates output audio data specific to the audio source, resulting in directional speech separation between different audio sources.

Abstract: A loudspeaker parameter system for vented box driver excursion modeling, may include a loudspeaker driver having a conductor, a magnet and a diaphragm. The system may further include a processor for excursion modeling configured to receive an input signal, determine a voltage level of the input signal, an enclosure having a resonant port, estimate port parameters including at least one of an acoustic resistance or acoustic mass, and apply a voltage limit based on the vented box excursion model utilizing the port parameters.

Abstract: A method and an apparatus for recognizing a voice are provided. The method may include: inputting a target voice into a pre-trained voice recognition model to obtain an initial text output by at least one recognition network in the voice recognition model, the recognition network including a plurality of preset types of processing layers, and at least one type of processing layer of the recognition network being obtained by training based on a voice sample in a preset direction interval; and determining a voice recognition result of the target voice, based on the initial text.

Abstract: In one aspect, a network microphone device includes a plurality of microphones and is configured to detect sound via the one or more microphones. The network microphone device may capture sound data based on the detected sound in a first buffer, and capture metadata associated with the detected sound in a second buffer. The network microphone device may classify one or more noises in the detected sound and cause the network microphone device to perform an action based on the classification of the respective one or more noises.

Abstract: A computer-implemented method and a computer program product for device pairing by cognitive computing. A cognitive computing system creates a knowledge corpus about the historical activities of pairing devices of a user. The cognitive computing system predicts needs of device pairing of the user, based on analysis of the historical activities. The cognitive computing system identifies devices that can be paired in a surrounding area. An augmented reality device tracks an eye direction of the user at a device, extrapolates the eye direction to create an eye focus direction of the user, obtains from the cognitive computing system an eye focus line with an arrow pointing to the device, and creates an augmented reality overlay which shows the eye focus line. The augmented reality device pairs a user currently used device and the device, upon user approval.

Abstract: In some embodiments, a method for processing an audio signal in an audio processing apparatus is disclosed. The method includes receiving an audio signal and a parameter, the parameter indicating a location of an auditory event boundary. An audio portion between consecutive auditory event boundaries constitutes an auditory event. The method further includes applying a modification to the audio signal based in part on an occurrence of the auditory event. The parameter may be generated by monitoring a characteristic of the audio signal and identifying a change in the characteristic.

Abstract: 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.

Abstract: Aspects of the invention include a method including collecting, by a processor, physiological data from a user in an environment and a sound waveform from the user's environment. The method detects and labels as a potential annoyance, by the processor, a set of potential annoyance data based on the collected physiological data and the sound waveform. The method decomposes, by the processor, the sound waveform into a first sound waveform segment associated with the set of potential annoyance data and a second sound waveform segment not associated with the set of potential annoyance data. The method predicts, by the processor, that the potential annoyance is an actual annoyance. The method filters and modifies, by the processor, the first sound waveform segment associated with the actual annoyance and provides, by the processor, the second sound waveform segment not associated with the actual annoyance to the user.

Abstract: A system accesses a first digital audio file that includes a plurality of spoken instructions. The system converts the first digital audio file to a first spectrogram image, applies a filter to determine whether an image quality of the first spectrogram image is below a predetermined image quality, and in response, generates a second spectrogram image from the first spectrogram image using a training model. The system converts the second spectrogram image to a second digital audio file and converts the second digital audio file into multiple vectors that each correspond to a particular spoken instruction. The system identifies related vectors and concatenates the related vectors together in order to create a plurality of concatenated vectors. The system generates, using the plurality of concatenated vectors, a third digital audio file that includes concatenated spoken instructions from the first digital audio file.

Abstract: An audio system presented herein includes a transducer array, sensor array, and a controller. The controller control tactile content imparted to a user via actuation of at least one transducer in the transducer array while presenting audio content to the user. The transducer array presents the audio content with the tactile content to the user. The audio system can be part of a headset.

Abstract: Aspects of the present disclosure are directed to use with communications that may involve repetitive communications. As may be implemented in accordance with one or more embodiments, a subset of symbols in a current data message (130/131) are used with a corresponding subset of symbols in a previous data message (120/121), to ascertain whether the current data message is a repetition of the previous data message. This may involve, for instance, generating a resemblance metric to represent semblance between a subset the data symbols of the current data message and a subset the data symbols of the previous data message (102). The resemblance metric can be used in determining whether the current data message is a repetition of the previous data message. This approach may be useful, for example, in ascertaining whether the current message is a repetition without necessarily decoding the message.

Abstract: In one embodiment, a multi-microphone system for an endpoint device receives input signals for a remote conference between the endpoint device and at least one other endpoint device. The multi-microphone system may include at least a top microphone unit and a bottom microphone unit. A signal degradation event that causes degradation of signals received by the top microphone unit or the bottom microphone unit is detected. Then, based on information regarding the signal degradation event, it is determined whether the signal degradation event affects one or both of the top microphone unit and the bottom microphone unit. In response, an output signal is generated for transmission to the at least one other endpoint device, and the output signal uses a portion of the input signals that excludes signals received by the top microphone unit and/or the bottom microphone unit determined to be affected by the signal degradation event.

Abstract: Disclosed embodiments may relate to systems and methods for monitoring and/or mapping noise data from a plurality of noise monitoring devices. In some embodiments, the plurality of noise monitoring devices may include hearing protection devices configured to detect noise, and typically may communicate such noise data (which may also include location) so that the noise data can be pooled. The pooled noise data from the plurality of noise monitoring devices may then be used to the benefit of one or more of such noise monitoring devices.

Abstract: 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.

Abstract: Example methods, systems, and articles of manufacture may relate to an aerial vehicle. The methods, systems, and articles of manufacture may include receiving an audio signal with a microphone of the aerial vehicle. The methods, systems, and articles of manufacture may also include processing the audio signal to determine at least one of a distance and type of aircraft located near the aerial vehicle. Additionally, the methods, systems, and articles of manufacture may include, based on the determination, performing at least one maneuver of the aerial vehicle.

Abstract: The present invention is a system and method using a hand-mounted force sensor to verify installation of a CPA-enabled electrical connector. The system has at least one CPA-enabled electrical connector with a locking button; at least one hand-mounted force sensor; an interface board; a transmission channel; a system processor; a non-transitory computer readable memory element; a display; and an input. The hand-mounted force sensors have an electrical output that is proportional to the force. By interposing a force sensor between the locking button and the source of force, the force to close the locking tab can be read.

Abstract: According to an exemplary embodiment, a content control device for a content divided into multiple playback sections includes at least one memory storing executable instructions and a processor that implements the executable instructions to execute a plurality of tasks. The plurality of tasks include a selecting task, a first acquiring task and an outputting task. The selecting task selects a playback section among the multiple playback sections. The first acquiring task acquires a first operation value in response to an operation of a first operation unit. The outputting task that outputs a plurality of parameter values. The plurality of parameter values are used for varying the content in the selected playback section, corresponding to the acquired first operation value based on control data that defines a relationship between the first operation value and the plurality of parameter values.

Abstract: An ear-mountable listening device includes an array of microphones physically arranged into a ring pattern to capture sounds from an environment and output first audio signals that are representative of the sounds captured by the microphones. A speaker is arranged to emit audio into an ear in response to a second audio signal. Electronics are coupled to the array of microphones and the speaker and configured to capture the sounds with the array of microphones to generate the first audio signals and generate the second audio signal that drives the speaker based upon one or more of the first audio signals.

Abstract: A hearing aid comprises a) a multitude of M input transducers each providing an electric input signal representative of environment sound in a time-frequency representation (k, l), and each comprise varying amounts of target (s) and noise (v) signal components; b) a signal processor configured to process said multitude of electric input signals; and comprising a beamformer filter configured to receive said multitude M of electric input signals and to provide a spatially filtered signal and a post-filter configured to receive said spatially filtered signal and to provide an estimate ?(k,l) of a target signal representing said target signal components from said target sound source. The signal processor is configured to provide estimates of power spectral densities ?s(k,l) of said target signal components in dependence of inter-frequency bin relationships between the spectral components enforced by properties of the electric input signals across at least some of said frequency bins.

Abstract: An acoustic noise reduction (ANR) headphone described herein has current detection circuitry that detects current consumed by an acoustic driver amplifier as a result of pressure changes due to a tapping of the headphone. Tapping may be performed to change an audio feature or operating mode of the audio system for the headphone. The current detection circuitry senses a characteristic of the current consumed by the acoustic driver amplifier that can be used to determine an occurrence of a tap event. Examples of a characteristic include an amplitude, waveform or duration of the sensed current. Advantageously, the ANR headphones avoid the need for control buttons to initiate the desired changes to the audio feature or operating mode.

Abstract: Embodiments include an audio system comprising an audio device, a speaker, and a processor. The audio system is configured to receive data from one or more sensors corresponding to persons in a room and/or characteristics of a room, and responsively take action to modify one or more characteristics of the audio system, share the information with other systems or devices, and track data over time to determine patterns and trends in the data.

Abstract: Techniques for adaptive cross-correlation are discussed. A first signal is received from a first audio sensor associated with a vehicle and a second signal is received from a second audio sensor associated with the vehicle. Techniques may include determining, based at least in part on the first signal, a first transformed signal in a frequency domain. Additionally, the techniques include determining, based at least in part on the second signal, a second transformed signal in the frequency domain. A parameter can be determined based at least in part on a characteristic associated with at least one of the vehicle, an environment proximate the vehicle, or one or more of the first or second signal. Cross-correlation data can be determined based at least in part on one or more of the first transformed signal, the second transformed signal, or the parameter.

Abstract: A method is provided for synchronizing a source device with a sink device. The source device transmits a stream of packets to the sink device. The source device receives feedback from the sink device indicating packet arrival times of the packets at the sink device. Based on the feedback, in some aspects, the source device determines an average time shift in the packet arrival times at the sink device, wherein the average time shift is relative to expected packet arrival times of the packets at the sink device. In some such aspects, the source device detects that the average time shift exceeds a threshold, and in response to the detecting, adjusts a streaming time of the stream of packets to synchronize, within a predefined tolerance, the source device with the sink device.

Abstract: An audio cancellation system includes a voice enabled computing system that is connected to an audio output device using a wired or wireless communication network. The voice enabled computing device can provide media content to a user and receive a voice command from the user. The connection between the voice enabled computing system and the audio output device introduces a time delay between the media content being generated at the voice enabled computing device and the media content being reproduced at the audio output device. The system operates to determine a calibration value adapted for the voice enabled computing system and the audio output device. The system uses the calibration value to filter the user's voice command from a recording of ambient sound including the media content, without requiring significant use of memory and computing resources.

Abstract: A display control device includes a control unit that displays a sound pressure level distribution of predetermined sound data and a recordable range corresponding to a quantization bit depth during recording of the sound data on a display unit.

Abstract: A method and apparatus for mobile emulator determination using sound fingerprinting is disclosed. The method includes a verification computer system receiving a transaction request from a computing device purporting to be a mobile device. Responsive to receiving the request, the verification computer system transmits a request for verification information to the computing device. The verification system includes information regarding a tone to be generated by a speaker of the computing device. Thereafter, verification information is received from the computing device. The verification information includes information tone information generated by the computing device, wherein the tone is, after generation, detected by a microphone. The verification system then verifies, based on the receive verification information, whether the information indicates that the computing device is a mobile device.