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Local Features (LFs) Based Bangla Phoneme Recognition: Local Feature or Mel Frequency Cepstral Coefficients - Which One is Better for MLN-Based Bangla Speech Recognition?

Mohammad Nasiruddin




[PDF.ao42] Local Features (LFs) Based Bangla Phoneme Recognition: Local Feature or Mel Frequency Cepstral Coefficients - Which One is Better for MLN-Based Bangla Speech Recognition?

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 |  2012-01-18 | Original language:English | PDF # 1 |  8.66 x.19 x5.91l,.30 | File type: PDF | 84 pages

||About the Author|Mohammad Nasiruddin has obtained his Masters degree in Computer Science & Engineering in 2011. Since then he has worked in different international projects in the field of Bangla Speech Recognition & Software Engineering. He is the author of sev

This monograph discusses the dominance of Local Features (LFs), as input to the Multilayer Neural Network (MLN), extracted from a Bangla input speech over Mel Frequency Cepstral Coefficients (MFCCs). Here, LF-based method comprises three stages- (i) LF extraction from input speech, (ii) Phoneme probabilities extraction using MLN from LF and (iii) The Hidden Markov Model (HMM) based classifier to obtain more accurate phoneme strings. In the experiments on Bangla speech c...

You easily download any file type for your gadget.Local Features (LFs) Based Bangla Phoneme Recognition: Local Feature or Mel Frequency Cepstral Coefficients - Which One is Better for MLN-Based Bangla Speech Recognition?   |  Mohammad Nasiruddin. Just read it with an open mind because none of us really know.

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