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1. 发明申请

US20090177468A1 SPEECH RECOGNITION WITH NON-LINEAR NOISE REDUCTION ON MEL-FREQUENCY CEPTRA 有权
标题翻译：语音识别与非线性噪声减少在频率CEPTRA
公开(公告)号：US20090177468A1
公开(公告)日：2009-07-09
申请号：US11970537
申请日：2008-01-08
申请人： Dong Yu , Alejandro Acero , James G. Droppo , Li Deng
发明人： Dong Yu , Alejandro Acero , James G. Droppo , Li Deng
IPC分类号： G10L15/20
CPC分类号： G10L15/20 , G10L15/02 , G10L21/02 , G10L25/24
摘要： In an automatic speech recognition system, a feature extractor extracts features from a speech signal, and speech is recognized by the automatic speech recognition system based on the extracted features. Noise reduction as part of the feature extractor is provided by feature enhancement in which feature-domain noise reduction in the form of Mel-frequency cepstra is provided based on the minimum means square error criterion. Specifically, the devised method takes into account the random phase between the clean speech and the mixing noise. The feature-domain noise reduction is performed in a dimension-wise fashion to the individual dimensions of the feature vectors input to the automatic speech recognition system, in order to perform environment-robust speech recognition.
摘要翻译：在自动语音识别系统中，特征提取器从语音信号中提取特征，并且基于提取的特征，通过自动语音识别系统识别语音。通过特征增强提供降噪作为特征提取器的一部分，其中基于最小均方误差准则提供了以Mel-frequency cepstra形式的特征域降噪。具体来说，设计的方法考虑了清洁语音和混合噪声之间的随机相位。为了执行环境鲁棒的语音识别，特征域噪声降低以维度方式执行到输入到自动语音识别系统的特征向量的各个维度。

2. 发明授权

US08306817B2 Speech recognition with non-linear noise reduction on Mel-frequency cepstra 有权
标题翻译：在梅尔频率cepstra上进行非线性降噪的语音识别
公开(公告)号：US08306817B2
公开(公告)日：2012-11-06
申请号：US11970537
申请日：2008-01-08
申请人： Dong Yu , Alejandro Acero , James G. Droppo , Li Deng
发明人： Dong Yu , Alejandro Acero , James G. Droppo , Li Deng
IPC分类号： G10L15/00
CPC分类号： G10L15/20 , G10L15/02 , G10L21/02 , G10L25/24
摘要： In an automatic speech recognition system, a feature extractor extracts features from a speech signal, and speech is recognized by the automatic speech recognition system based on the extracted features. Noise reduction as part of the feature extractor is provided by feature enhancement in which feature-domain noise reduction in the form of Mel-frequency cepstra is provided based on the minimum means square error criterion. Specifically, the devised method takes into account the random phase between the clean speech and the mixing noise. The feature-domain noise reduction is performed in a dimension-wise fashion to the individual dimensions of the feature vectors input to the automatic speech recognition system, in order to perform environment-robust speech recognition.
摘要翻译：在自动语音识别系统中，特征提取器从语音信号中提取特征，并且基于提取的特征，通过自动语音识别系统识别语音。通过特征增强提供降噪作为特征提取器的一部分，其中基于最小均方误差准则提供了以Mel-frequency cepstra形式的特征域降噪。具体来说，设计的方法考虑了清洁语音和混合噪声之间的随机相位。为了执行环境鲁棒的语音识别，特征域噪声降低以维度方式执行到输入到自动语音识别系统的特征向量的各个维度。

3. 发明授权

US07769582B2 Method of pattern recognition using noise reduction uncertainty 有权
标题翻译：使用降噪不确定度的模式识别方法
公开(公告)号：US07769582B2
公开(公告)日：2010-08-03
申请号：US12180260
申请日：2008-07-25
申请人： James G. Droppo , Alejandro Acero , Li Deng
发明人： James G. Droppo , Alejandro Acero , Li Deng
IPC分类号： G10L15/20 , G10L21/02 , G10L15/14
CPC分类号： G10L21/0208 , G10L15/20
摘要： A method and apparatus are provided for using the uncertainty of a noise-removal process during pattern recognition. In particular, noise is removed from a representation of a portion of a noisy signal to produce a representation of a cleaned signal. In the meantime, an uncertainty associated with the noise removal is computed and is used with the representation of the cleaned signal to modify a probability for a phonetic state in the recognition system. In particular embodiments, the uncertainty is used to modify a probability distribution, by increasing the variance in each Gaussian distribution by the amount equal to the estimated variance of the cleaned signal, which is used in decoding the phonetic state sequence in a pattern recognition task.
摘要翻译：提供了一种在模式识别期间使用噪声去除处理的不确定性的方法和装置。特别地，从噪声信号的一部分的表示中去除噪声以产生清洁信号的表示。同时，计算与噪声去除有关的不确定性，并与清除信号的表示一起使用以修改识别系统中语音状态的概率。在特定实施例中，不确定性用于通过将每个高斯分布中的方差增加等于在模式识别任务中对语音状态序列进行解码所使用的清除信号的估计方差的量来修改概率分布。

4. 发明授权

US07447630B2 Method and apparatus for multi-sensory speech enhancement 有权
标题翻译：多感官语音增强的方法和装置
公开(公告)号：US07447630B2
公开(公告)日：2008-11-04
申请号：US10724008
申请日：2003-11-26
申请人： Zicheng Liu , Michael J. Sinclair , Alejandro Acero , Xuedong D. Huang , James G. Droppo , Li Deng , Zhengyou Zhang , Yanli Zheng
发明人： Zicheng Liu , Michael J. Sinclair , Alejandro Acero , Xuedong D. Huang , James G. Droppo , Li Deng , Zhengyou Zhang , Yanli Zheng
IPC分类号： G10L21/02
CPC分类号： G10L21/0208 , G10L2021/02165
摘要： A method and system use an alternative sensor signal received from a sensor other than an air conduction microphone to estimate a clean speech value. The estimation uses either the alternative sensor signal alone, or in conjunction with the air conduction microphone signal. The clean speech value is estimated without using a model trained from noisy training data collected from an air conduction microphone. Under one embodiment, correction vectors are added to a vector formed from the alternative sensor signal in order to form a filter, which is applied to the air conductive microphone signal to produce the clean speech estimate. In other embodiments, the pitch of a speech signal is determined from the alternative sensor signal and is used to decompose an air conduction microphone signal. The decomposed signal is then used to determine a clean signal estimate.
摘要翻译：一种方法和系统使用从除空气传导麦克风以外的传感器接收的替代传感器信号来估计干净的语音值。该估计单独使用替代传感器信号，或者与导气麦克风信号一起使用。无需使用从空气传导麦克风收集的噪声训练数据训练的模型来估计干净的语音值。在一个实施例中，校正矢量被添加到由替代传感器信号形成的矢量中，以形成滤波器，该滤波器被施加到空气传导麦克风信号以产生干净的语音估计。在其他实施例中，语音信号的音调由替代传感器信号确定，并用于分解空气传导麦克风信号。然后使用分解的信号来确定干净的信号估计。

5. 发明授权

US07460992B2 Method of pattern recognition using noise reduction uncertainty 有权
标题翻译：使用降噪不确定度的模式识别方法
公开(公告)号：US07460992B2
公开(公告)日：2008-12-02
申请号：US11435254
申请日：2006-05-16
申请人： James G. Droppo , Alejandro Acero , Li Deng
发明人： James G. Droppo , Alejandro Acero , Li Deng
IPC分类号： G10L15/20 , G10L21/02
CPC分类号： G10L21/0208 , G10L15/20
摘要： A method and apparatus are provided for using the uncertainty of a noise-removal process during pattern recognition. In particular, noise is removed from a representation of a portion of a noisy signal to produce a representation of a cleaned signal. In the meantime, an uncertainty associated with the noise removal is computed and is used with the representation of the cleaned signal to modify a probability for a phonetic state in the recognition system. In particular embodiments, the uncertainty is used to modify a probability distribution, by increasing the variance in each Gaussian distribution by the amount equal to the estimated variance of the cleaned signal, which is used in decoding the phonetic state sequence in a pattern recognition task.
摘要翻译：提供了一种在模式识别期间使用噪声去除处理的不确定性的方法和装置。特别地，从噪声信号的一部分的表示中去除噪声以产生清洁信号的表示。同时，计算与噪声去除有关的不确定性，并与清除信号的表示一起使用以修改识别系统中语音状态的概率。在特定实施例中，不确定性用于通过将每个高斯分布中的方差增加等于在模式识别任务中对语音状态序列进行解码所使用的清除信号的估计方差的量来修改概率分布。

6. 发明授权

US07174292B2 Method of determining uncertainty associated with acoustic distortion-based noise reduction 有权
公开(公告)号：US07174292B2
公开(公告)日：2007-02-06
申请号：US10236042
申请日：2002-09-05
申请人： Li Deng , Alejandro Acero , James G. Droppo
发明人： Li Deng , Alejandro Acero , James G. Droppo
IPC分类号： G10L15/20 , G10L21/02
CPC分类号： G10L15/20 , G10L21/0208
摘要： A method and apparatus are provided for determining uncertainty in noise reduction based on a parametric model of speech distortion. The method is first used to reduce noise in a noisy signal. In particular, noise is reduced from a representation of a portion of a noisy signal to produce a representation of a cleaned signal by utilizing an acoustic environment model. The uncertainty associated with the noise reduction process is then computed. In one embodiment, the uncertainty of the noise reduction process is used, in conjunction with the noise-reduced signal, to decode a pattern state.

7. 发明授权

US07725314B2 Method and apparatus for constructing a speech filter using estimates of clean speech and noise 有权
标题翻译：用于使用干净的语音和噪声的估计来构造语音滤波器的方法和装置
公开(公告)号：US07725314B2
公开(公告)日：2010-05-25
申请号：US10780177
申请日：2004-02-16
申请人： Jian Wu , James G. Droppo , Li Deng , Alejandro Acero
发明人： Jian Wu , James G. Droppo , Li Deng , Alejandro Acero
IPC分类号： G10L15/20 , G10L21/02 , G10L15/00 , H04B15/00
CPC分类号： G10L21/0208
摘要： A method and apparatus identify a clean speech signal from a noisy speech signal. To do this, a clean speech value and a noise value are estimated from the noisy speech signal. The clean speech value and the noise value are then used to define a gain on a filter. The noisy speech signal is applied to the filter to produce the clean speech signal. Under some embodiments, the noise value and the clean speech value are used in both the numerator and the denominator of the filter gain, with the numerator being guaranteed to be positive.
摘要翻译：方法和装置从噪声语音信号中识别干净的语音信号。为此，从噪声语音信号估计干净的语音值和噪声值。然后使用干净的语音值和噪声值来定义滤波器上的增益。噪声语音信号被施加到滤波器以产生干净的语音信号。在一些实施例中，噪声值和清洁语音值用于滤波器增益的分子和分母，分子保证为正。

8. 发明授权

US07542900B2 Noise reduction using correction vectors based on dynamic aspects of speech and noise normalization 有权
标题翻译：基于语音和噪声归一化的动态方面的校正矢量降噪
公开(公告)号：US07542900B2
公开(公告)日：2009-06-02
申请号：US11429630
申请日：2006-05-05
申请人： James G. Droppo , Li Deng , Alejandro Acero
发明人： James G. Droppo , Li Deng , Alejandro Acero
IPC分类号： G10L21/02
CPC分类号： G10L21/0208
摘要： A method and apparatus are provided for reducing noise in a signal. Under one aspect of the invention, a correction vector is selected based on a noisy feature vector that represents a noisy signal. The selected correction vector incorporates dynamic aspects of pattern signals. The selected correction vector is then added to the noisy feature vector to produce a cleaned feature vector. In other aspects of the invention, a noise value is produced from an estimate of the noise in a noisy signal. The noise value is subtracted from a value representing a portion of the noisy signal to produce a noise-normalized value. The noise-normalized value is used to select a correction value that is added to the noise-normalized value to produce a cleaned noise-normalized value. The noise value is then added to the cleaned noise-normalized value to produce a cleaned value representing a portion of a cleaned signal.
摘要翻译：提供了一种降低信号噪声的方法和装置。在本发明的一个方面，基于表示噪声信号的噪声特征向量来选择校正矢量。所选择的校正矢量包含模式信号的动态方面。然后将所选择的校正向量加到噪声特征向量中以产生清除的特征向量。在本发明的其他方面，噪声值是由噪声信号中的噪声的估计产生的。从表示噪声信号的一部分的值中减去噪声值，以产生噪声归一化值。噪声归一化值用于选择加到噪声归一化值的校正值以产生清洁的噪声归一化值。然后将噪声值添加到清洁的噪声归一化值，以产生表示清洁信号的一部分的清洁值。

9. 发明授权

US07165026B2 Method of noise estimation using incremental bayes learning 有权
标题翻译：使用增量式贝叶斯学习的噪声估计方法
公开(公告)号：US07165026B2
公开(公告)日：2007-01-16
申请号：US10403638
申请日：2003-03-31
申请人： Alejandro Acero , Li Deng , James G. Droppo
发明人： Alejandro Acero , Li Deng , James G. Droppo
IPC分类号： G10L15/00 , G10L21/00
CPC分类号： G10L21/0208
摘要： A method and apparatus estimate additive noise in a noisy signal using incremental Bayes learning, where a time-varying noise prior distribution is assumed and hyperparameters (mean and variance) are updated recursively using an approximation for posterior computed at the preceding time step. The additive noise in time domain is represented in the log-spectrum or cepstrum domain before applying incremental Bayes learning. The results of both the mean and variance estimates for the noise for each of separate frames are used to perform speech feature enhancement in the same log-spectrum or cepstrum domain.
摘要翻译：一种方法和装置使用增量贝叶斯学习估计噪声信号中的加性噪声，其中假定时变噪声预先分布，并且使用在前一时间步长计算的后验近似来递归地更新超参数（均值和方差）。在应用增量贝叶斯学习之前，在对数谱或倒频谱域中表示时域中的加性噪声。用于每个单独帧的噪声的平均值和方差估计的结果用于在相同的对数谱或倒频谱域中执行语音特征增强。

10. 发明授权

US07117148B2 Method of noise reduction using correction vectors based on dynamic aspects of speech and noise normalization 有权
公开(公告)号：US07117148B2
公开(公告)日：2006-10-03
申请号：US10117142
申请日：2002-04-05
申请人： James G. Droppo , Li Deng , Alejandro Acero
发明人： James G. Droppo , Li Deng , Alejandro Acero
IPC分类号： G10L21/02
CPC分类号： G10L21/0208
摘要： A method and apparatus are provided for reducing noise in a signal. Under one aspect of the invention, a correction vector is selected based on a noisy feature vector that represents a noisy signal. The selected correction vector incorporates dynamic aspects of pattern signals. The selected correction vector is then added to the noisy feature vector to produce a cleaned feature vector. In other aspects of the invention, a noise value is produced from an estimate of the noise in a noisy signal. The noise value is subtracted from a value representing a portion of the noisy signal to produce a noise-normalized value. The noise-normalized value is used to select a correction value that is added to the noise-normalized value to produce a cleaned noise-normalized value. The noise value is then added to the cleaned noise-normalized value to produce a cleaned value representing a portion of a cleaned signal.

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