Title :
Bangla phoneme recognition for different acoustic features
Author :
Kotwal, Mohammed Rokibul Alam ; Hassan, Foyzul ; Banik, Manoj ; Islam, Gazi Md Moshfiqul ; Rakibuzzaman, Md ; Hasan, Mohammad Mahedi ; Muhammad, Ghulam ; Huda, Mohammad Nurul
Author_Institution :
United Int. Univ., Dhaka, Bangladesh
Abstract :
In this paper, we compare among performance of different acoustic features for Bangla Automatic Speech Recognition (ASR). Most of the Bangla 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) and local features (LFs) are inputted to the hidden Markov model (HMM) based classifiers for obtaining phoneme recognition performance. It is shown from the experimental results that MFCC-based method of 39 dimensions provides a higher phoneme correct rate and accuracy than the other methods investigated.
Keywords :
hidden Markov models; speech recognition; Bangla phoneme recognition; acoustic feature recognition; automatic speech recognition system; hidden Markov model; local features; mel frequency cepstral coefficients; Computer applications; Conferences; Industrial electronics; Automatic Speech Recognition; Hidden Markov Model; Local Features; Mel-frequency Cepstral Coefficients;
Conference_Titel :
Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-9054-7
DOI :
10.1109/ICCAIE.2010.5735140
