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Modified MFCC methods based on KL- transform and power law for robust speech recognition
Published in Little Lion Scientific
2014
Volume: 67
   
Issue: 2
Pages: 527 - 532
Abstract

This paper presents robust feature extraction techniques, called Mel Power Karhunen Loeve Transform Coefficients (MPKC), Mel Power Coefficients (MPC) for an isolated digit recognition. This hybrid method involves Stevens’ Power Law of Hearing and Karhunen Loeve(KL) Transform to improve noise robustness. We have evaluated the proposed methods on a Hidden Markov Model (HMM) based isolated digit recognition system with TIDIGITS data for clean speech and also with noisy speech data. An increase in the recognition accuracy rate is observed with the proposed methods compared to conventional Mel Frequency Cepstral Coefficients (MFCC) technique. © 2005 - 2014 JATIT & LLS. All rights reserved.

About the journal
JournalJournal of Theoretical and Applied Information Technology
PublisherLittle Lion Scientific
ISSN19928645