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Cepstrum PDF Normalization Method for Speech Recognition in Noise Environment  

Suk Yong Ho (㈜엠큐브웍스)
Lee Hwang-Soo (한국과학기술원 전자전산학과)
Choi Seung Ho (서울산업대학교 전자정보공학과)
Publication Information
The Journal of the Acoustical Society of Korea / v.24, no.4, 2005 , pp. 224-229 More about this Journal
Abstract
In this paper, we Propose a novel cepstrum normalization method which normalizes the probability density function (pdf) of cepstrum for robust speech recognition in additive noise environments. While the conventional methods normalize the first- and/or second-order statistics such as the mean and/or variance of the cepstrum. the proposed method fully normalizes the statistics of cepstrum by making the pdfs of clean and noisy cepstrum identical to each other For the target Pdf, the generalized Gaussian distribution is selected to consider various densities. In recognition phase, we devise a table lookup method to save computational costs. From the speaker-independent isolated-word recognition experiments, we show that the Proposed method gives improved Performance compared with that of the conventional methods, especially in heavy noise environments.
Keywords
Speech Recognition; Cepstrum; Normalization; Pdf;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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