Abstract: A device capable of autonomous motion may move in an environment and may receive audio data from a microphone. A model may be trained to process the audio data to suppress noise from the audio data. The model may include an encoder that includes one or more convolutional layers, one or more recurrent layers, and a decoder that includes one or more convolutional layers.

Abstract: A device capable of autonomous motion may move in an environment and may receive audio data from a microphone. A model may be trained to process the audio data to determine mask data, which may be used to mask noise in the audio data. Training data for the model may be normalized before training, and different loss functions may be used for different types of training data.

Abstract: A computing device may receive audio data from a microphone representing audio in an environment of the device, which may correspond to an utterance and noise. A model may be trained to process the audio data to cancel noise from the audio data. The model may include an encoder that includes one or more dense layers, one or more recurrent layers, and a decoder that includes one or more dense layers.

Abstract: An ear-worn electronic device includes a right ear device comprising a first processor and a left ear device comprising a second processor communicatively coupled to the first processor. A physiologic sensor module comprises one or more physiologic sensors configured to sense at least one physiologic parameter from a wearer. A motion sensor module comprises one or more sensors configured to sense movement of the wearer. The first and second processors are coupled to the physiologic and motion sensor modules. The first and second processors are configured to produce a three-dimensional virtual sound environment comprising relaxing sounds, generate verbal instructions within the three-dimensional virtual sound environment that guide the wearer through a predetermined mental exercise that promotes wearer relaxation, and generate verbal commentary that assesses wearer compliance with the predetermined mental exercise in response to one or both of the sensed movement and the at least one physiologic parameter.

Abstract: A device capable of motion includes a beamformer for determining audio data corresponding to one or more directions. The beamformer includes a target beamformer that boosts audio from a target direction and a null beamformer that suppresses audio from that direction. When the device outputs sound while moving, the target and null beamformers capture and compensate for Doppler effects in output audio that reflects from nearby surfaces back to the device.

Abstract: A device capable of moving a component of the device motion is capable of determining audio data corresponding to a direction relative to the device (“beamforming”). When the component moves, the device determines a new position of the component and selects one of a set of beamforming filter coefficients corresponding to the position. Using the filter coefficients, the device determines the directional audio data.

Abstract: A system configured to improve echo cancellation for nonlinear systems. The system generate reference audio data by isolating portions of microphone audio data that correspond to playback audio data. For example, the system may determine a correlation between the playback audio data and the microphone audio data in individual time-frequency bands in a frequency domain. In some examples, the system may substitute microphone audio data associated with output audio for the playback audio data. The system may generate the reference audio data based on portions of the microphone audio data that have a strong correlation with the playback audio data. The system may generate the reference audio data by selecting these portions of the microphone audio data or by performing beamforming. This results in precise time alignment between the reference audio data and the microphone audio data, improving performance of the echo cancellation.

Abstract: An ear-worn electronic device includes a right ear device comprising a first processor and a left ear device comprising a second processor communicatively coupled to the first processor. A physiologic sensor module comprises one or more physiologic sensors configured to sense at least one physiologic parameter from a wearer. A motion sensor module comprises one or more sensors configured to sense movement of the wearer. The first and second processors are coupled to the physiologic and motion sensor modules. The first and second processors are configured to produce a three-dimensional virtual sound environment comprising relaxing sounds, generate verbal instructions within the three-dimensional virtual sound environment that guide the wearer through a predetermined mental exercise that promotes wearer relaxation, and generate verbal commentary that assesses wearer compliance with the predetermined mental exercise in response to one or both of the sensed movement and the at least one physiologic parameter.

Abstract: An ear-worn electronic device includes a right ear device comprising a first processor and a left ear device comprising a second processor communicatively coupled to the first processor. A physiologic sensor module comprises one or more physiologic sensors configured to sense at least one physiologic parameter from a wearer. A motion sensor module comprises one or more sensors configured to sense movement of the wearer. The first and second processors are coupled to the physiologic and motion sensor modules. The first and second processors are configured to produce a three-dimensional virtual sound environment comprising relaxing sounds, generate verbal instructions within the three-dimensional virtual sound environment that guide the wearer through a predetermined mental exercise that promotes wearer relaxation, and generate verbal commentary that assesses wearer compliance with the predetermined mental exercise in response to one or both of the sensed movement and the at least one physiologic parameter.

Abstract: An audio processing device is described comprising an energy distribution determiner configured to determine an energy distribution of a sound and an acoustical environment determiner configured to determine based on the energy distribution whether the sound includes a sound caused by the acoustical environment.

Abstract: Techniques are disclosed for position-robust multiple microphone noise estimation techniques. The position-robust noise estimation techniques can be used when receiving speech including diffuse noise sources, which is commonly encountered in noisy environments. The position-robust noise estimation techniques include detecting speech using the power level difference (PLD) and the coherence statistics (CS) between two microphone input signals. This multi-dimensional approach results in dual microphone noise estimation which is not affected by the position of the audio input device, resulting in more accurate detection of speech periods and more accurate noise estimation results. The position-robust noise estimate obtained from the techniques can then be used as part of a noise reduction system to reduce the levels of noise in noisy speech signals.

Abstract: An ear-worn electronic device includes a right ear device comprising a first processor and a left ear device comprising a second processor communicatively coupled to the first processor. A physiologic sensor module comprises one or more physiologic sensors configured to sense at least one physiologic parameter from a wearer. A motion sensor module comprises one or more sensors configured to sense movement of the wearer. The first and second processors are coupled to the physiologic and motion sensor modules. The first and second processors are configured to produce a three-dimensional virtual sound environment comprising relaxing sounds, generate verbal instructions within the three-dimensional virtual sound environment that guide the wearer through a predetermined mental exercise that promotes wearer relaxation, and generate verbal commentary that assesses wearer compliance with the predetermined mental exercise in response to one or both of the sensed movement and the at least one physiologic parameter.

Abstract: Wind noise reduction is described for audio signals received in a device. In one embodiment, an audio signal is decomposed into a plurality of sub-bands, the audio signal including wind noise, a first sub-band of the plurality of sub-bands low-pass filtered, wind noise is removed from the first sub band and the first sub-band is combined with the other sub-bands after removing wind noise.

Abstract: Techniques are disclosed for position-robust multiple microphone noise estimation techniques. The position-robust noise estimation techniques can be used when receiving speech including diffuse noise sources, which is commonly encountered in noisy environments. The position-robust noise estimation techniques include detecting speech using the power level difference (PLD) and the coherence statistics (CS) between two microphone input signals. This multi-dimensional approach results in dual microphone noise estimation which is not affected by the position of the audio input device, resulting in more accurate detection of speech periods and more accurate noise estimation results. The position-robust noise estimate obtained from the techniques can then be used as part of a noise reduction system to reduce the levels of noise in noisy speech signals.

Abstract: In one example a controller comprises logic, at least partially including hardware logic, configured to detect speech activity in an audio signal received in a non-aerial microphone and in response to the voice activity, to apply a noise cancellation algorithm to a speech input received in a aerial microphone. Other examples may be described.

Abstract: An audio processing device is described comprising an energy distribution determiner configured to determine an energy distribution of a sound and an acoustical environment determiner configured to determine based on the energy distribution whether the sound includes a sound caused by the acoustical environment.

Abstract: A noise reduction device may be provided. The noise reduction device may include: an input configured to receive an input signal including a representation in a frequency domain of an audio signal, wherein the representation includes a plurality of time frames and a plurality of coefficients for each time frame; a noise detection circuit configured to determine a first indicator being indicative of a bandwidth of a coefficient over at least two time; a noise reduction circuit configured to reduce based on the first indicator a noise component in the audio signal; and an output configured to output an output signal including a representation in the frequency domain of the audio signal with the reduced noise component.

Abstract: Wind noise reduction is described for audio signals received in a device. In one embodiment, an audio signal is decomposed into a plurality of sub-bands, the audio signal including wind noise, a first sub-band of the plurality of sub-bands low-pass filtered, wind noise is removed from the first sub band and the first sub-band is combined with the other sub-bands after removing wind noise.

Abstract: A device and a method reduce direction dependent spatial noise. The device includes a plurality of microphones for measuring an acoustic input signal from an acoustic source. The plurality of microphones form at least one monaural pair and at least one binaural pair. Directional signal processing circuitry is provided for obtaining, from the input signal, at least one monaural directional signal and at least one binaural directional signal. A target signal level estimator estimates a target signal level by combining at least one of the monaural directional signals and at least one of the binaural directional signals, which at least one monaural directional signal and at least one binaural directional signal mutually have a maximum response in a direction of the acoustic source.

Abstract: A noise reduction device may be provided. The noise reduction device may include: an input configured to receive an input signal including a representation in a frequency domain of an audio signal, wherein the representation includes a plurality of time frames and a plurality of coefficients for each time frame; a noise detection circuit configured to determine a first indicator being indicative of a bandwidth of a coefficient over at least two time; a noise reduction circuit configured to reduce based on the first indicator a noise component in the audio signal; and an output configured to output an output signal including a representation in the frequency domain of the audio signal with the reduced noise component.