首页> 外文会议>International Conference on Computational Science - ICCA 2003 Pt.1 Jun 2-4, 2003 Melbourne, Australia and St. Petersburg, Russia >On the Extraction of the Valid Speech-Sound by the Merging Algorithm with the Discrete Wavelet Transform
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On the Extraction of the Valid Speech-Sound by the Merging Algorithm with the Discrete Wavelet Transform

机译:基于离散小波变换的融合算法提取有效语音

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摘要

A valid speech-sound block can be classified to provide important information for speech recognition. The classification of the speech-sound block comes from the MR A (multi-resolution analysis) property of the DWT(discrete wavelet transform), which is used to reduce the computational time for the pre-processing of speech recognition. The merging algorithm is proposed to extract valid speech-sounds in terms of position and frequency range. It needs some numerical methods for an adaptive DWT implementation and performs unvoiced/voiced classification and denoising. Since the merging algorithm can decide the processing parameters relating to voices only and is independent of system noises, it is useful for extracting valid speech-sounds. The merging algorithm has an adaptive feature for arbitrary system noises and an excellent denoising SNR (signal-to-noise ratio).
机译:可以对有效的语音块进行分类,以提供用于语音识别的重要信息。语音块的分类来自DWT(离散小波变换)的MR A(多分辨率分析)属性,该属性用于减少语音识别预处理的计算时间。提出了一种融合算法,以根据位置和频率范围提取有效的语音。它需要一些数值方法来实现自适应DWT,并执行清音/清音分类和去噪。由于合并算法只能确定与语音相关的处理参数,并且与系统噪声无关,因此对于提取有效的语音很有用。合并算法具有针对任意系统噪声的自适应功能和出色的降噪SNR(信噪比)。

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