NDLI: Bangla triphone HMM based word recognition

Content Provider	IEEE Xplore Digital Library
Author	Hasan, M.M. Hassan, F. Islam, G.M.M. Banik, M. Kotwal, M.R.A. Rahman, S.M.M. Muhammad, G. Mohammad, N.H.
Copyright Year	2010
Description	Author affiliation: Enosis Solutions, Dhaka, Bangladesh (Hassan, F.) \|\| Department of CSE, United International University, Dhaka, Bangladesh (Islam, G.M.M.; Kotwal, M.R.A.; Rahman, S.M.M.) \|\| Department of CE, College of CIS, King Saud University, Riyadh, Kingdom of Saudi Arabia (Muhammad, G.; Mohammad, N.H.) \|\| Department of CSE, Ahsanullah University of Science and Technology, Dhaka, Bangladesh (Banik, M.) \|\| Blueliner Bangladesh, Dhaka, Bangladesh (Hasan, M.M.)
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.
Starting Page	883
Ending Page	886
File Size	464186
Page Count	4
File Format	PDF
ISBN	9781424474547
e-ISBN	9781424474561
DOI	10.1109/APCCAS.2010.5775010
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-06
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech recognition Hidden Markov models Speech Mel frequency cepstral coefficient DH-HEMTs Artificial neural networks Asia triphone model mel-frequency cepstral coefficients hidden Markov model automatic speech recognition
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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