Papers

Mean normalization of power function based cepstral coefficients for robust speech recognition in noisy environment

International Conference
2011~2015
작성자
한혜원
작성일
2014-05-01 00:42
조회
300
Authors : Soonho Baek, Hong-Goo Kang

Year : 2014

Publisher / Conference : ICASSP

This paper presents the effect of mean normalization to various types of cepstral coefficients for robust speech recognition in noisy environments. Although the cepstral mean normalization (CMN) technique was originally designed to compensate channel distortion, it has also been proved that the CMN also improves recognition accuracy in additive noisy environment. However, no one has yet considered the interaction of CMN with spectral mapping functions required for extracting cepstral features. This paper investigates the impact of CMN to the speech recognition system depending on the types of spectral mapping function by mathematically analyzing the amount of spectral distortion between clean and noisy conditions. The analytic result is also confirmed by comparing the type of recognition error patterns in automatic speech recognition experiment with Aurora 2 database. Experimental results show that the performance improvement by adopting CMN becomes significant if the logarithmic function is replaced with the appropriate setting of fractional power mapping function. Especially, the deletion errors are dramatically reduced.
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71 International Conference Soonho Baek, Hong-Goo Kang "Mean normalization of power function based cepstral coefficients for robust speech recognition in noisy environment" in ICASSP, 2014
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65 International Conference Jae-Mo Yang, Hong-Goo Kang "Adaptive multichannel linear prediction based dereverberation in time-varying room environments" in EUSIPCO, 2013
64 International Conference JeeSok Lee, Frank Soong, Hong-Goo Kang "Source-Filter based Full-band Adaptive Harmonic Model and Its Application to Speech Prosody Modification" in INTERSPEECH, 2013
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