Method of improving voice quality using a wireless headset with untethered earbuds starts by receiving first acoustic signal from first microphone included in first untethered earbud and receiving second acoustic signal from second microphone included in second untethered earbud. First inertial sensor output is received from first inertial sensor included in first earbud and second inertial sensor output is received from second inertial sensor included in second earbud. First earbud processes first noise/wind level captured by first microphone, first acoustic signal and first inertial sensor output and second earbud processes second noise/wind level captured by second microphone, second acoustic signal, and second inertial sensor output. First and second noise/wind levels and first and second inertial sensor outputs are communicated between the earbuds. First earbud transmits first acoustic signal and first inertial sensor output when first noise and wind level is lower than second noise/wind level. Other embodiments are described.

A sound processing device includes a processor configured to generate a first frequency spectrum of a first sound signal corresponding to a first sound received at a first input device and a second frequency spectrum of a second sound signal corresponding to the first sound received at a second input device, calculate a transfer characteristic based on a first difference between an intensity of the first frequency spectrum and an intensity of the second frequency spectrum, generate a third frequency spectrum of a third sound signal transmitted from the first input device and a fourth frequency spectrum of a fourth sound signal transmitted from the second input device, specify a suppression level of an intensity of the fourth frequency spectrum based on a second difference between an intensity of the third frequency spectrum and an intensity of the fourth frequency spectrum.

Provided are methods and systems for acoustic keystroke transient cancellation/suppression for user communication devices using a semi-blind adaptive filter model. The methods and systems are designed to overcome existing problems in transient noise suppression by taking into account some less-defective signal as side information on the transients and also accounting for acoustic signal propagation, including the reverberation effects, using dynamic models. The methods and systems take advantage of a synchronous reference microphone embedded in the keyboard of the user device, and utilize an adaptive filtering approach exploiting the knowledge of this keybed microphone signal.

A voice recognition system in a vehicle includes: a first microphone mounted in the vehicle that collects voice data of an occupant of the vehicle; a second microphone provided in a mobile device of the occupant that collects voice data of the occupant; and a voice recognition device connected to the mobile device through local wireless communication including a noise elimination portion eliminating noise in the voice data collected by the first microphone or the second microphone and a voice recognition portion performing voice recognition using the voice data from which noise is eliminated by the noise elimination portion.

Embodiments of the present disclosure set forth a method or reducing noise in an audio environment. The method includes acquiring, via one or more sensors, a plurality of audio signals associated with sound in an audio environment; determining that a first audio signal in the plurality of audio signals matches a first reference signal in a set of reference signals; generating, based on the first audio signal, a first directional audio signal wherein, when the first directional audio signal is outputted by a loudspeaker, the loudspeaker produces a first acoustic field that attenuates the first audio signal at a position of a user; determining that a second audio signal in the plurality of audio signals does not match at least one reference signal in the set of reference signals; and storing data associated with the second audio signal as an additional reference signal in the set of reference signals.

A method of operation of a device includes receiving an input signal at the device. The input signal is generated using at least one microphone. The input signal includes a first signal component having a first amount of wind turbulence noise and a second signal component having a second amount of wind turbulence noise that is greater than the first amount of wind turbulence noise. The method further includes generating, based on the input signal, an output signal at the device. The output signal includes the first signal component and a third signal component that replaces the second signal component. A first frequency response of the input signal corresponds to a second frequency response of the output signal.

A selective audio source enhancement system includes a processor and a memory, and a pre-processing unit configured to receive audio data including a target audio signal, and to perform sub-band domain decomposition of the audio data to generate buffered outputs. In addition, the system includes a target source detection unit configured to receive the buffered outputs, and to generate a target presence probability corresponding to the target audio signal, as well as a spatial filter estimation unit configured to receive the target presence probability, and to transform frames buffered in each sub-band into a higher resolution frequency-domain. The system also includes a spectral filtering unit configured to retrieve a multichannel image of the target audio signal and noise signals associated with the target audio signal, and an audio synthesis unit configured to extract an enhanced mono signal corresponding to the target audio signal from the multichannel image.

Provided are methods and systems for acoustic keystroke transient cancellation/suppression for user communication devices using a semi-blind adaptive filter model. The methods and systems are designed to overcome existing problems in transient noise suppression by taking into account some less-defective signal as side information on the transients and also accounting for acoustic signal propagation, including the reverberation effects, using dynamic models. The methods and systems take advantage of a synchronous reference microphone embedded in the keyboard of the user device, and utilize an adaptive filtering approach exploiting the knowledge of this keybed microphone signal.

A selective audio source enhancement system includes a processor and a memory, and a pre-processing unit configured to receive audio data including a target audio signal, and to perform sub-band domain decomposition of the audio data to generate buffered outputs. In addition, the system includes a target source detection unit configured to receive the buffered outputs, and to generate a target presence probability corresponding to the target audio signal, as well as a spatial filter estimation unit configured to receive the target presence probability, and to transform frames buffered in each sub-band into a higher resolution frequency-domain. The system also includes a spectral filtering unit configured to retrieve a multichannel image of the target audio signal and noise signals associated with the target audio signal, and an audio synthesis unit configured to extract an enhanced mono signal corresponding to the target audio signal from the multichannel image.

A speech processing device includes a distance acquisition unit configured to acquire a distance between a sound collection unit configured to record speech from a sound source and the sound source, a reverberation characteristic estimation unit configured to estimate a reverberation characteristic based on the distance acquired by the distance acquisition unit, a correction data generation unit configured to generate correction data indicating a contribution of a reverberation component from the reverberation characteristic estimated by the reverberation characteristic estimation unit; and a dereverberation unit configured to remove the reverberation component from the speech by correcting the amplitude of the speech based on the correction data.