Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/5964
Title: An improved GA based modified dynamic neural network for Cantonese-digit speech recognition
Authors: Ling, SH
Leung, FHF 
Leung, KF
Lam, HK
Iu, HHC
Keywords: Neural network
Issue Date: 6-Jan-2007
Publisher: InTech
Source: In M Grimm and K Kroschel (Eds.), Robust speech recognition and understanding, p. 363-384. InTech, 2007 How to cite?
Abstract: In this chapter, a dynamic neural network tuned by an improved GA (Lam et al., 2004) is proposed. New genetic operations (crossover and mutation) will be introduced. Rules have been introduced to the crossover process to make offspring widely spread along the domain. A fast convergence rate can be reached. A different process of mutation has been applied.
This chapter is organized as follows. The genetic algorithm with improved genetic operations will be briefly described in section 2. The specific structure of the proposed dynamic neural network will be presented in section 3. In section 4, a Cantonese-digit speech recognition system will be discussed. The results for recognizing thirteen Cantonese digits and a conclusion will be given in section 5 and 6 respectively.
URI: http://hdl.handle.net/10397/5964
ISBN: 978-3-902613-08-0
DOI: 10.5772/4760
Rights: The article is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported <http://creativecommons.org/licenses/by-nc-sa/3.0/>
Appears in Collections:Book Chapter

Files in This Item:
File Description SizeFormat 
Ling_GA_Neural_Network.pdf250.29 kBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

171
Last Week
4
Last month
Checked on May 21, 2017

Download(s)

71
Checked on May 21, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.