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    Unified deep neural network model for acoustic echo cancellation and residual echo suppression
    2.
    发明授权
    Unified deep neural network model for acoustic echo cancellation and residual echo suppression 有权

    公开(公告)号：US11776556B2

    公开(公告)日：2023-10-03

    申请号：US17485943

    申请日：2021-09-27

    申请人： TENCENT AMERICA LLC

    发明人： Meng Yu ,  Dong Yu

    IPC分类号： G10L21/0224 ,  H04R3/04 ,  G06N3/02 ,  G10L21/0216 ,  G10L21/0208

    CPC分类号： G10L21/0224 ,  G06N3/02 ,  H04R3/04 ,  G10L2021/02082 ,  G10L2021/02163

    摘要： A method, computer program, and computer system is provided for an all-deep-learning based AEC system by recurrent neural networks. The model consists of two stages, echo estimation stage and echo suppression stage, respectively. Two different schemes for echo estimation are presented herein: linear echo estimation by multi-tap filtering on far-end reference signal and non-linear echo estimation by single-tap masking on microphone signal. A microphone signal waveform and a far-end reference signal waveform are received. An echo signal waveform is estimated based on the microphone signal waveform and a far-end reference signal waveform. A near-end speech signal waveform is output based on subtracting the estimated echo signal waveform from the microphone signal waveform, and echoes are suppressed within the near-end speech signal waveform.

    Method and apparatus for suppressing wind noise
    5.
    发明授权
    Method and apparatus for suppressing wind noise 有权

    公开(公告)号：US09916841B2

    公开(公告)日：2018-03-13

    申请号：US15177807

    申请日：2016-06-09

    申请人： 2236008 Ontario Inc.

    发明人： Phillip Alan Hetherington ,  Xueman Li ,  Pierre Zakarauskas

    IPC分类号： G10L21/0232 ,  H04B15/00 ,  G10L21/0208 ,  G10L21/0264 ,  G10L21/0216

    CPC分类号： G10L21/0232 ,  G10L21/0208 ,  G10L21/0264 ,  G10L2021/02163 ,  H04R2410/07

    摘要： The invention includes a method, apparatus, and computer program to selectively suppress wind noise while preserving narrow-band signals in acoustic data. Sound from one or several microphones is digitized into binary data. A time-frequency transform is applied to the data to produce a series of spectra. The spectra are analyzed to detect the presence of wind noise and narrow band signals. Wind noise is selectively suppressed while preserving the narrow band signals. The narrow band signal is interpolated through the times and frequencies when it is masked by the wind noise. A time series is then synthesized from the signal spectral estimate that can be listened to. This invention overcomes prior art limitations that require more than one microphone and an independent measurement of wind speed. Its application results in good-quality speech from data severely degraded by wind noise.

    Audio signal noise attenuation
    7.
    发明授权
    Audio signal noise attenuation 有权

    公开(公告)号：US09875748B2

    公开(公告)日：2018-01-23

    申请号：US14351646

    申请日：2012-10-22

    申请人： KONINKLIJKE PHILIPS N.V.

    发明人： Sriram Srinivasan

    IPC分类号： G10L21/02 ,  G10L19/012 ,  G10L21/0208 ,  G10L21/0216

    CPC分类号： G10L19/012 ,  G10L21/02 ,  G10L21/0202 ,  G10L21/0208 ,  G10L21/0216 ,  G10L2021/02163 ,  G10L2021/02165 ,  G10L2021/02166

    摘要： A noise attenuation apparatus receives an audio signal comprising a desired and a noise signal component. Two codebooks (109, 111) comprise respectively desired signal candidates representing a possible desired signal component and noise signal contribution candidates representing possible noise contributions. A segmenter (103) segments the audio signal into time segments and for each time segment a noise attenuator (105) generates estimated signal candidates by for each of the desired signal candidates generating an estimated signal candidate as a combination of a scaled version of the desired signal candidate and a weighted combination of the noise signal contribution candidates. The noise attenuator (105) minimizes a cost function indicative of a difference between the estimated signal candidate and the audio signal in the time segment. A signal candidate is then determined for the time segment from the estimated signal candidates and the audio signal is noise compensated based on this signal candidate.

    METHOD AND APPARATUS FOR ELIMINATING MUSIC NOISE VIA A NONLINEAR ATTENUATION/GAIN FUNCTION
    10.
    发明申请
    METHOD AND APPARATUS FOR ELIMINATING MUSIC NOISE VIA A NONLINEAR ATTENUATION/GAIN FUNCTION 有权
    通过非线性衰减/增益函数消除音乐噪声的方法和装置

    公开(公告)号：US20160064010A1

    公开(公告)日：2016-03-03

    申请号：US14829052

    申请日：2015-08-18

    申请人： Marvell World Trade Ltd.

    发明人： Jin Xie ,  Kapil Jain

    IPC分类号： G10L21/0264 ,  G10L21/0316 ,  G10L25/21

    CPC分类号： G10L21/0264 ,  G10L19/0204 ,  G10L21/0232 ,  G10L21/0316 ,  G10L25/21 ,  G10L2021/02085 ,  G10L2021/02163

    摘要： A system including first and second gain modules, an operator module, and a priori and posteriori modules. The first gain module applies a non-linear function to generate a gain signal based on an amplitude of a first speech signal and an estimated a priori variance of noise included in the first speech signal. The operator module generates an operator based on the gain signal and the estimated a priori variance of noise. The a priori module determines an a priori signal-to-noise ratio based on the operator. The posteriori module determines a posteriori signal-to-noise ratio based on the amplitude of the first speech signal and (ii) the estimated a priori variance of noise. The second gain module: determines a gain value based on the a priori signal-to-noise ratio and the a posteriori signal-to-noise ratio; and generates, based on the amplitude of the first speech signal and the gain value, a second speech signal that corresponds to an estimate of an amplitude of the first speech signal, where the second speech signal is substantially void of music noise.

    摘要翻译： 包括第一增益模块和第二增益模块的系统，操作模块和先验和后验模块。 第一增益模块应用非线性函数，以基于第一语音信号的幅度和包括在第一语音信号中的估计的噪声的先验方差来产生增益信号。 操作员模块基于增益信号和估计的噪声的先验方差来生成操作者。 先验模块基于操作者确定先验信噪比。 后验模块基于第一语音信号的幅度确定后验信噪比，以及（ii）所估计的先验噪声方差。 第二增益模块：基于先验信噪比和后验信噪比来确定增益值; 并且基于第一语音信号和增益值的幅度生成对应于第一语音信号的幅度的估计的第二语音信号，其中第二语音信号基本上没有音乐噪声。