DocumentCode :
3231711
Title :
Bangla triphone HMM based word recognition
Author :
Hasan, Mohammad Mahedi ; Hassan, Foyzul ; Islam, Gazi Md Moshfiqul ; Banik, Manoj ; Kotwal, Mohammed Rokibul Alam ; Rahman, Sharif Mohammad Musfiqur ; Muhammad, Ghulam ; Mohammad, Nurul Huda
Author_Institution :
Blueliner Bangladesh, Dhaka, Bangladesh
fYear :
2010
fDate :
6-9 Dec. 2010
Firstpage :
883
Lastpage :
886
Abstract :
In this paper, we have prepared a medium size Bangla speech corpus and compare performances of different acoustic features for Bangla word recognition. Most of the Bangla automatic speech recognition (ASR) system uses a small number of speakers, but 40 speakers selected from a wide area of Bangladesh, where Bangla is used as a native language, are involved here. In the experiments, mel-frequency cepstral coefficients (MFCCs) are inputted to the triphone hidden Markov model (HMM) based classifiers for obtaining word recognition performance. From the experiments, it is shown that MFCC-based method of 39 dimensions provides a higher word correct rate (WCR) and word accuracy (WA) than the other methods investigated. Moreover, a higher WCR and WA is obtained by the MFCC39-based method with fewer mixture components in the HMM.
Keywords :
cepstral analysis; hidden Markov models; speech recognition; Bangla triphone HMM; MFCC39-based method; automatic speech recognition system; hidden Markov model based classifiers; medium size Bangla speech corpus; mel-frequency cepstral coefficients; word accuracy; word correct rate; word recognition; Artificial neural networks; Asia; DH-HEMTs; Hidden Markov models; Mel frequency cepstral coefficient; Speech; Speech recognition; automatic speech recognition; hidden Markov model; mel-frequency cepstral coefficients; triphone model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems (APCCAS), 2010 IEEE Asia Pacific Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-7454-7
Type :
conf
DOI :
10.1109/APCCAS.2010.5775010
Filename :
5775010
Link To Document :
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