Isolated Digit Recognition Using in Ear Microphone Data Using MFCC,VQ and HMM

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2014 by IJETT Journal
Volume-12 Number-7
Year of Publication : 2014
Authors : Mahesh K. Patil , Prof. Dr.(Mrs.) L.S. Admuthe , Prashant P. Zirmite
  10.14445/22315381/IJETT-V12P264

MLA 

Mahesh K. Patil , Prof. Dr.(Mrs.) L.S. Admuthe , Prashant P. Zirmite. "Isolated Digit Recognition Using in Ear Microphone Data Using MFCC,VQ and HMM", International Journal of Engineering Trends and Technology (IJETT), V12(7),322-325 June 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract

This paper implements the isolated digit recognizer in three steps. The first step performs the endpoint detection and speech segmentation by short term analysis. The second step involves the speech feature extraction by using Mel Frequency Cepstral Coefficients (MFCC) parameters. Finally the third step involves the Vector Quantization (VQ) – Hidden Markov Model (HMM) based classifier for isolated digit recognition. An English spoken digit database which contains number of speakers is used for the testing and validation modules.

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References
Speaker recognition, MFCC, Vector Quantization, Hidden Markov Model.