Speech Recognition System Using a Wavelet Packet and Synergetic Neural Network

Author

Bai Maorui ; Feng Mingming ; Zheng Yuzheng

Author_Institution

Dept. of Commun. Eng., Chengdu Univ. of Inf. Technol., Chengdu, China

Volume

3

fYear

2010

fDate

13-14 March 2010

Firstpage

453

Lastpage

456

Abstract

A recognition system is proposed, for audio and speech signal processing, which based on a Wavelet Packet (WP) and Synergetic Neural Network (SNN). Firstly, in the step of features extraction, the Mel-frequency cepstral coefficients (MFCC) algorithm is developed by using WP instead of FT. Secondly, we make use of SNN to pattern recognition. Due to the Kohonen rule,the SNN can be combined with improved MFCC very well in the system. Finally, the experiment results show that the speech recognition system has higher recognition rate and potential advantages in automatic speech recognition.

Keywords

feature extraction; neural nets; speech recognition; Mel-frequency cepstral coefficients; audio signal processing; feature extraction; speech recognition system; speech signal processing; synergetic neural network; wavelet packet; Automatic speech recognition; Cepstral analysis; Feature extraction; Mel frequency cepstral coefficient; Neural networks; Pattern recognition; Signal processing algorithms; Speech processing; Speech recognition; Wavelet packets; Kohonen rule; MFCC; Speech Recognition System; Synergetic Neural Network; Wavelet Packet;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on

Conference_Location

Changsha City

Print_ISBN

978-1-4244-5001-5

Electronic_ISBN

978-1-4244-5739-7

Type

conf

DOI

10.1109/ICMTMA.2010.572

Filename

5458884