The Improved MFCC Speech Feature Extraction Method and its Application

Article Preview

Abstract:

Based on traditional MFCC feature, this paper suggests a new kind of speech signal feature: CMFCC by introducing the method of nonlinear properties. Simulation results indicate that the method has a strong robust to noise and is able to enhance the recognition rate under low SNR.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

4059-4062

Citation:

Online since:

September 2013

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Chen Liwei. Chinese speech recognition based on HMM and ANN[J]. Harbin: Harbin Engineering University. 2005: 29-30.

Google Scholar

[2] Ma Weirong, Feng Hongwei, Li Ning. Speech endpoint detection algorithm based on C0 complexity and energy[J]. Computer Engineering and Applications. 2009. 45(27) : 143-145.

Google Scholar

[3] Josef RAJNOHA, Petri POLLAK. Modified Feature Extraction Methods in Robust Speech Recognition[C]. IEEE tans Speech and audio processing. 2007. 8(4): 245-246.

DOI: 10.1109/radioelek.2007.371488

Google Scholar

[4] Sandipan Chakroborty, Anindya Roy. Capturing Complementary Information via Reversed Filter Bank And parallel implementation with MFCC for improved Text-Independent Speaker Identification[C]. Proceedings of the international Conference on Computing. 2007. 2(20): 432-434.

DOI: 10.1109/iccta.2007.35

Google Scholar

[5] Zhang Xichun, Cao Yan, Zhang Jun, Wei Gang. Improved Extraction Algorithm for MFCC Feature[J]. Data Acquisition and Processing. 2005-07. 20(2): 161-165.

Google Scholar