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MODEL-BASED DISTORTION COMPENSATING NOISE REDUCTION APPARATUS AND METHOD FOR SPEECH RECOGNITION
MODEL-BASED DISTORTION COMPENSATING NOISE REDUCTION APPARATUS AND METHOD FOR SPEECH RECOGNITION
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机译:语音识别的基于模型的失真补偿噪声降低装置及方法
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摘要
A model-based distortion compensating noise reduction apparatus for speech recognition, includes: a speech absence probability calculator for calculating the probability distribution for absence and existence of a speech using the sound absence and existence information for the frames; a noise estimation updater for estimating a more accurate noise component by updating the variance of the clean speech and noise for each frame; and a speech absence probability-based noise filter for outputting a first clean speech through the speech absence probability transmitted from the speech absence probability calculator and a first noise filter. Further, the model-based distortion compensating noise reduction apparatus includes a post probability calculator for calculating post probabilities for mixtures using a GMM containing a clean speech in the first clean speech; and a final filter designer for forming a second noise filter and outputting an improved final clean speech signal using the second noise filter.
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