Noise Robust Novel Approach to Speech Recognition

Swapnil D. Daphal, S. Jagtap
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引用次数: 2

Abstract

Most practical methods of the speech recognition (SR) are dependent on the feature extraction schemes used in the implementation. The performances of these SR systems are highly affected by the presence of noise. By passing speech signal through cochlear filter bank (CFB) prior to the feature extraction reduces the impact of the noise on the system. In this paper, noise robust approach of feature extraction, cochlear filter bank with zero crossing as a feature is discussed. The comparative analysis of CFB with Mel frequency Cepstral Coefficients (MFCC) approach of feature extraction in terms of recognition accuracy (RA) is discussed. It may be implied that former approach gave a good fit to the experimentation in presence of noise.
噪声鲁棒语音识别新方法
大多数实用的语音识别方法都依赖于实现中使用的特征提取方案。这些SR系统的性能受噪声的影响很大。在特征提取之前,将语音信号通过耳蜗滤波器组(CFB),减少了噪声对系统的影响。本文讨论了以零交叉为特征的耳蜗滤波器组的噪声鲁棒特征提取方法。讨论了CFB与Mel频率倒谱系数(MFCC)特征提取方法在识别精度方面的对比分析。这可能意味着,前一种方法对存在噪声的实验具有良好的拟合性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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