NDLI: Dialect identification based on VQ codebook design with GA-LBG algorithm

Content Provider	IEEE Xplore Digital Library
Author	Yan He Feng Qin Yu
Copyright Year	2011
Description	Author affiliation: School of Internet of Things Engineering, Jiangnan University, Wuxi, China (Yan He; Feng Qin Yu)
Abstract	In order to solve the problem of GA's slow convergence in the VQ codebook design due to the strong global search ability and the complex computation, a hybrid algorithm based on the GA-LBG algorithm is adopted because the LBG algorithm as an iterative algorithm based on the nearest neighbor rule and the centroid rule owns the advantage of fast convergence. In the simulation experiment, MFCC extracted from Mandarin, Shanghainese, Cantonese and Hokkien are employed as the feature vectors to establish codebook models with GA-LBG for the dialect identification, and the recognition performances on different size of the VQ codebooks are studied. And simulation results demonstrate that the running time with GA-LBG reduces to 1066.4s, less than that with GA alone.
Starting Page	94
Ending Page	97
File Size	139567
Page Count	4
File Format	PDF
ISBN	9781424495993
e-ISBN	9781424496006
DOI	10.1109/CCIENG.2011.6008075
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Training Vector quantization Clustering algorithms Speech recognition GA-LBG algorithm Speech Mel frequency cepstral coefficient MFCC Genetic algorithms Dialect identification
Content Type	Text
Resource Type	Article

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