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    • 5. 发明授权
    • Method of pattern recognition using noise reduction uncertainty
    • 使用降噪不确定度的模式识别方法
    • US07769582B2
    • 2010-08-03
    • US12180260
    • 2008-07-25
    • James G. DroppoAlejandro AceroLi Deng
    • James G. DroppoAlejandro AceroLi Deng
    • G10L15/20G10L21/02G10L15/14
    • G10L21/0208G10L15/20
    • 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.
    • 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
    • Method of pattern recognition using noise reduction uncertainty
    • 使用降噪不确定度的模式识别方法
    • US07460992B2
    • 2008-12-02
    • US11435254
    • 2006-05-16
    • James G. DroppoAlejandro AceroLi Deng
    • James G. DroppoAlejandro AceroLi Deng
    • G10L15/20G10L21/02
    • G10L21/0208G10L15/20
    • 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.
    • 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。
    • 8. 发明授权
    • Speech recognition with non-linear noise reduction on Mel-frequency cepstra
    • 在梅尔频率cepstra上进行非线性降噪的语音识别
    • US08306817B2
    • 2012-11-06
    • US11970537
    • 2008-01-08
    • Dong YuAlejandro AceroJames G. DroppoLi Deng
    • Dong YuAlejandro AceroJames G. DroppoLi Deng
    • G10L15/00
    • G10L15/20G10L15/02G10L21/02G10L25/24
    • 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.
    • 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。
    • 10. 发明授权
    • Noise reduction using correction vectors based on dynamic aspects of speech and noise normalization
    • 基于语音和噪声归一化的动态方面的校正矢量降噪
    • US07181390B2
    • 2007-02-20
    • US11189974
    • 2005-07-26
    • James G. DroppoLi DengAlejandro Acero
    • James G. DroppoLi DengAlejandro Acero
    • G10L21/02
    • G10L21/0208
    • 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.
    • 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。