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Method and apparatus for robust extraction of features for the speech recognition

机译:用于语音识别的特征的鲁棒提取的方法和设备

摘要

The present invention relates to a method and an apparatus for a robust feature extraction for speech recognition in a noisy environment, wherein the speech signal is segmented and is characterized by spectral components. The speech signal is splitted into a number of short term spectral components in L subbands, with L = 1,2,...and a noise spectrum from segments that only contain noise is estimated. Then a spectral subtraction of the estimated noise spectrum from the corresponding short term spectrum is performed and a probability for each short term spectrum component to contain noise is calculated. Finally these spectral component of each short-term spectrum, having a low probability to contain speech are interpolated in order to smooth those short-term spectra that only contain noise. With the interpolation the spectral components containing noise are interpolated by reliable spectral speech components that could be found in the neighborhood.
机译:本发明涉及一种用于在嘈杂环境中进行语音识别的鲁棒特征提取的方法和设备,其中语音信号被分段并且由频谱分量表征。语音信号被分成L个子带中的多个短期频谱分量,L = 1,2,...,并且仅包含噪声的段的噪声谱被估计。然后,从相应的短期频谱对估计的噪声频谱进行频谱减法,并计算每个短期频谱分量包含噪声的概率。最后,内插每个短期频谱的频谱成分,这些频谱成分包含语音的可能性很小,以便平滑那些仅包含噪声的短期频谱。通过内插,可以在附近找到可靠的频谱语音分量,对包含噪声的频谱分量进行内插。

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