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    ACOUSTIC REMOTE CONTROL INTERFACE FOR HEADSETS
    21.
    发明公开
    ACOUSTIC REMOTE CONTROL INTERFACE FOR HEADSETS 审中-公开

    公开(公告)号：US20240241690A1

    公开(公告)日：2024-07-18

    申请号：US18428214

    申请日：2024-01-31

    Applicant: Intel Corporation

    Inventor： Sebastian Rosenkiewicz ,  Adam Kupryjanow ,  Lukasz Pindor

    IPC: G06F3/16 ,  H04R1/10

    CPC classification number: G06F3/165 ,  H04R1/1041 ,  H04R2430/01

    Abstract: Techniques are provided herein for implementing headset control functions for low-end consumer-grade headsets using a firmware module implemented in the computing platform. The techniques can include a microphone mute function, a headset speaker volume function, and other headset functions. In particular, acoustic events are utilized to control headset functions. Because the headset control components are inside system firmware, the headset control module is endpoint agnostic and will work with any headset coupled to the computing platform. The computing device through which a voice call is implemented can include an event trigger detector, which detects selected acoustic events and triggers a corresponding action. The system allows for control of the voice call via custom user acoustic events. In some examples, the acoustic event that mutes the microphone can be a finger tap. A finger tap generally has a short duration and is easily detectable.

    REAL-TIME INFERENCE OF TEMPORAL DOWN-SAMPLING CONVOLUTIONAL NETWORKS
    22.
    发明公开
    REAL-TIME INFERENCE OF TEMPORAL DOWN-SAMPLING CONVOLUTIONAL NETWORKS 审中-公开

    公开(公告)号：US20240020517A1

    公开(公告)日：2024-01-18

    申请号：US18474564

    申请日：2023-09-26

    Applicant: Intel Corporation

    Inventor： Lukasz Pindor ,  Adam Kupryjanow

    IPC: G06N3/0464

    CPC classification number: G06N3/0464

    Abstract: Low latency neural network models are provided that can be used for speech processing. The neural networks allow for real-time inference of CNN models without an increase in computer complexity or memory footprint. Buffers are used for upsampling, and the depth of the convolutions varies by frame number. In some examples, a condition is applied within the convolution block to determine a depth of convolutions based on the frame number. In some examples, the network includes multiple convolution sub-model blocks, each having a different depth, and a table is used to select the convolution sub-model block for each frame based on the frame number. The neural networks can be used for speech enhancement tasks such as dynamic noise suppression (DNS), blind source separation (BSS), and Self-Noise Silencers (SNS).

    AUDIO-BASED DETECTION AND TRACKING OF EMERGENCY VEHICLES
    23.
    发明申请
    AUDIO-BASED DETECTION AND TRACKING OF EMERGENCY VEHICLES 审中-公开

    公开(公告)号：US20200213728A1

    公开(公告)日：2020-07-02

    申请号：US16814361

    申请日：2020-03-10

    Applicant: Intel Corporation

    Inventor： Kuba Lopatka ,  Adam Kupryjanow ,  Lukasz Kurylo ,  Karol Duzinkiewicz ,  Przemyslaw Maziewski ,  Marek Zabkiewicz

    IPC: H04R3/00 ,  H04R1/40 ,  G10L25/51 ,  G10L25/30 ,  G10L25/18 ,  H04R3/04 ,  G10L21/0232 ,  G06N3/08

    Abstract: 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.

    NOISE REDUCTION USING SPECIFIC DISTURBANCE MODELS
    24.
    发明申请
    NOISE REDUCTION USING SPECIFIC DISTURBANCE MODELS 审中-公开

    公开(公告)号：US20200184987A1

    公开(公告)日：2020-06-11

    申请号：US16786471

    申请日：2020-02-10

    Applicant: INTEL CORPORATION

    Inventor： Adam Kupryjanow ,  Kuba Lopatka ,  Tomasz Szmelczynski

    IPC: G10L21/0224 ,  G10L15/16 ,  G10L21/0232

    Abstract: An example apparatus for reducing noise in audio includes a preprocessor to receive audio input from a microphone and preprocess the audio input to generate preprocessed audio. The apparatus also includes an acoustic event detector to detect an acoustic event corresponding to a disturbance in the preprocessed audio. The apparatus further includes a noise reduction model selector to select a specific disturbance model based the detected acoustic event. The apparatus further includes a noise suppressor to attenuate components related to the disturbance in the preprocessed audio using the selected specific disturbance model to generate an enhanced audio with suppressed noise.

    NEURAL NETWORK BASED TIME-FREQUENCY MASK ESTIMATION AND BEAMFORMING FOR SPEECH PRE-PROCESSING
    26.
    发明申请
    NEURAL NETWORK BASED TIME-FREQUENCY MASK ESTIMATION AND BEAMFORMING FOR SPEECH PRE-PROCESSING 审中-公开

    公开(公告)号：US20190043491A1

    公开(公告)日：2019-02-07

    申请号：US16023455

    申请日：2018-06-29

    Applicant: INTEL CORPORATION

    Inventor： Adam Kupryjanow ,  Kuba Lopatka

    IPC: G10L15/20 ,  G10L15/16 ,  G10L25/84 ,  G10L21/0232

    Abstract: Techniques are provided for pre-processing enhancement of a speech signal. A methodology implementing the techniques according to an embodiment includes performing de-reverberation processing on signals received from an array of microphones, the signals comprising speech and noise. The method also includes generating time-frequency masks (TFMs) for each of the signals. The TFMs indicate the probability that a time-frequency component of the signal associated with that TFM element includes speech. The TFM generation is based on application of a recurrent neural network to the signals. The method further includes generating steering vectors based on speech covariance matrices and noise covariance matrices. The TFMs are employed to filter speech components of the signals, for calculation of the speech covariance, and noise components of the signals for calculation of the noise covariance. The method further includes performing beamforming on the signals, based on the steering vectors, to generate the enhanced speech signal.

    REAL-TIME DYNAMIC NOISE REDUCTION USING CONVOLUTIONAL NETWORKS
    29.
    发明申请
    REAL-TIME DYNAMIC NOISE REDUCTION USING CONVOLUTIONAL NETWORKS 有权

    公开(公告)号：US20250046304A1

    公开(公告)日：2025-02-06

    申请号：US18770496

    申请日：2024-07-11

    Applicant: Intel Corporation

    Inventor： Adam Kupryjanow ,  Tomasz Noczynski ,  Lukasz Pindor ,  Sebastian Rosenkiewicz

    IPC: G10L15/20 ,  G10L15/16

    Abstract: A system, method and computer readable medium for dynamic noise reduction in a voice call. The system includes an encoder having a short-time Fourier transform module to determine a magnitude spectrum and a phase spectrum of an input audio signal. The input audio signal includes speech and dynamic noise. A separator is coupled to the encoder. The separator comprises a temporal convolution network (TCN) used to develop a separation mask using the magnitude spectrum as input. The TCN is trained using a frequency SNR function used to calculate loss during training. A mixer is coupled to the separator to multiply the separation mask with the magnitude spectrum to separate the speech from the dynamic noise to obtain a denoise magnitude spectrum. The system also includes a decoder coupled to the mixer and the encoder. The decoder includes an inverse short-time Fourier transform module to reconstruct the input audio signal without the dynamic noise using the denoise magnitude spectrum and the phase spectrum.

    Noise reduction using specific disturbance models
    30.
    发明授权
    Noise reduction using specific disturbance models 有权

    公开(公告)号：US12211512B2

    公开(公告)日：2025-01-28

    申请号：US16786471

    申请日：2020-02-10

    Applicant: INTEL CORPORATION

    Inventor： Adam Kupryjanow ,  Kuba Lopatka ,  Tomasz Szmelczynski

    IPC: G10L21/0224 ,  G10L15/16 ,  G10L21/0216 ,  G10L21/0232

    Abstract: An example apparatus for reducing to reduce noise in audio includes a preprocessor to receive audio input from a microphone and preprocess the audio input to generate preprocessed audio. The apparatus also includes an acoustic event detector to detect an acoustic event corresponding to a disturbance in the preprocessed audio. The apparatus further includes a noise reduction model selector to select a specific disturbance model based on the detected acoustic event. The apparatus further includes a noise suppressor to attenuate components related to the disturbance in the preprocessed audio using the selected specific disturbance model to generate enhanced audio with suppressed noise.

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