Intel Corporation

Lukasz Kurylo

Przemyslaw Maziewski

Adam Kupryjanow

Georg Stemmer

Kuba Lopatka

Pawel Trella

Karol Duzinkiewicz

Tomasz Noczynski

Raghavendra Rao R

Sebastian Czyryba

Piotr Chlebek

Marek Zabkiewicz

Techniques are provided for audio-based detection and tracking of an acoustic source. A methodology implementing the techniques according to an embodiment includes generating acoustic signal spectra from signals provided by a microphone array, and performing beamforming on the acoustic signal spectra to generate beam signal spectra, using time-frequency masks to reduce noise. The method also includes detecting, by a deep neural network (DNN) classifier, an acoustic event, associated with the acoustic source, in the beam signal spectra. The DNN is trained on acoustic features associated with the acoustic event. The method further includes performing pattern extraction, in response to the detection, to identify time-frequency bins of the acoustic signal spectra that are associated with the acoustic event, and estimating a motion direction of the source relative to the array of microphones based on Doppler frequency shift of the acoustic event calculated from the time-frequency bins of the extracted pattern.

Audio-based detection and tracking of emergency vehicles

For a multiple microphone system, a phase response mismatch may be corrected. One embodiment includes receiving audio from a first microphone and from a second microphone, the microphones being coupled to a single device for combining the received audio, recording the received audio from the first microphone and the second microphone before combining the received audio, detecting a phase response mismatch in the recording at the device between the audio received at the second microphone and the audio received at the first microphone, if a phase response mismatch is detected, then estimating a phase delay between the second microphone and the first microphone, and storing the estimated phase delay for use in correcting the phase delay in received audio before combining the received audio.

Phase response mismatch correction for multiple microphones

A mechanism is described for facilitating automatic gain adjustment in audio systems according to one embodiment. A method of embodiments, as described herein, includes determining status of one or more of gain settings, mute settings, and boost settings associated with one or more microphones based on a configuration of a computing device including a voice-enabled device. The method may further comprise recommending adjustment of microphone gain based on the configuration and the status of one or more of the gain, mute, and boost settings, and applying the recommended adjustment of the microphone gain.

Automatic gain adjustment for improved wake word recognition in audio systems

An example apparatus for suppression of key phrase detection includes an audio receiver to receive generated audio from a loopback endpoint and captured audio from a microphone. The apparatus includes a self-trigger detector to detect a key phrase in the generated audio. The apparatus also includes a detection suppressor to suppress detection of the detected key phrase in the captured audio at a second key detector for a predetermined time in response to detecting the key phrase in the generated audio.

Suppressing key phrase detection in generated audio using self-trigger detector

A mechanism is described for facilitating simultaneous recognition and processing of multiple speeches from multiple users according to one embodiment. A method of embodiments, as described herein, includes facilitating a first microphone to detect a first speech from a first speaker, and a second microphone to detect a second speech from a second speaker. The method may further include facilitating a first beam-former to receive and process the first speech, and a second beam-former to receive and process the second speech, where the first and second speeches are at least received or processed simultaneously. The method may further include communicating a first output associated with the first speech and a second output associated with the second speech to the first speaker and the second speaker, respectively, using at least one of one or more speaker devices and one or more display devices.

Simultaneous multi-user audio signal recognition and processing for far field audio

Embodiments of a system and method for adapting a phase difference-based noise reduction system are generally described herein. In some embodiments, spatial information associated with a first and second audio signal are determined, wherein the first and second audio signals including a target audio inside a beam and noise from outside the beam. A signal-to-noise ratio (SNR) associated with the audio signals is estimated. A mapping of phase differences to gain factors is adapted for determination of attenuation factors for attenuating frequency bins associated with noise outside the beam. Spectral subtraction is performed to remove estimated noise from the single-channel signal based on a weighting that affects frequencies associated with a target signal less. Frequency dependent attenuation factors are applied to attenuate frequency bins outside the beam to produce a target signal having noise reduced.

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Gdansk, Poland

Lukasz Kurylo