I have completed my thesis of 18 credit hours during completing my Masters in Computer Science and Engineering at United International University. I have submitted and presented my paper to International Conference on Electrical, Computer and Telecommunication Engineering (ICECTE) - 2012. Here is a brief information of my paper below,
Paper Title: Normalization of Gender factor in Bangla ASR
Main Author: Engr. Md.Asfak-Ur-Rahman
Other Authors:
Abstract: "This paper presents a Bangla (widely used as Ben-gali) automatic speech recognition system (ASR) by suppressing gender effects. Gender characteristic plays an important role on the performance of ASR. If there is a suppression process that represses the decrease of differences in acoustic-likelihood among categories resulted from gender factors, a robust ASR system can be realized. In the proposed method, we have designed a new ASR incorporating the Local Features (LFs) instead of standard mel frequency cepstral coefficients (MFCCs) as an acoustic feature for Bangla by suppressing the gender effects, which embeds three HMM-based classifiers for corresponding male, female and geneder-independent (GI) characteristics. In the experiments on Bangla speech database prepared by us, the proposed system has achieved a significant improvement of word correct rates (WCRs), word accuracies (WAs) and sentence correct rates (SCRs) in comparison with the method that incorporates Standard MFCCs"
Keywords: Acoustic Model, Automatic Speech Recognition, Gender Effects Suppression, Hidden Markov Model
The concept and writing of this article are protected by copyright. Excepting translations, you may not reproduce this articles online or in print without first obtaining written permission. Please contact me to obtain my written consent.
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Paper Title: Normalization of Gender factor in Bangla ASR
Main Author: Engr. Md.Asfak-Ur-Rahman
Other Authors:
- B.K.M Mizanur Rahman
- Bulbul Ahamed
- Foyzul Hassan
- Mohammad Nurul Huda
Abstract: "This paper presents a Bangla (widely used as Ben-gali) automatic speech recognition system (ASR) by suppressing gender effects. Gender characteristic plays an important role on the performance of ASR. If there is a suppression process that represses the decrease of differences in acoustic-likelihood among categories resulted from gender factors, a robust ASR system can be realized. In the proposed method, we have designed a new ASR incorporating the Local Features (LFs) instead of standard mel frequency cepstral coefficients (MFCCs) as an acoustic feature for Bangla by suppressing the gender effects, which embeds three HMM-based classifiers for corresponding male, female and geneder-independent (GI) characteristics. In the experiments on Bangla speech database prepared by us, the proposed system has achieved a significant improvement of word correct rates (WCRs), word accuracies (WAs) and sentence correct rates (SCRs) in comparison with the method that incorporates Standard MFCCs"
Keywords: Acoustic Model, Automatic Speech Recognition, Gender Effects Suppression, Hidden Markov Model
Copyright Notice
Contact authors for permissionThe concept and writing of this article are protected by copyright. Excepting translations, you may not reproduce this articles online or in print without first obtaining written permission. Please contact me to obtain my written consent.
Include required attribution text
You must include the following text on the same page as your reprint and if the article is used in a print publication, the attribution must read:
"Reprinted with the permission of Engr. Md.Asfak-Ur-Rahman, asfak-ur-rahman.blogspot.com"Artwork and design cannot be reproduced
You may translate my articles into languages other than English, free of charge, without prior notice, and without soliciting our written permission, under the following conditions:
- Your publication must be freely available. You may not sell my content and concept that you have translated.
- You must faithfully translate the article and concept as written.Except for minor issues of vernacular, you may not alter the my meaning.
- You must link to my web page in which the article appeared, and must credit "Engr. Md.Asfak-Ur-Rahman, asfak-ur-rahman.blogspot.com". You may not claim to have written the material yourself. (But you know that.)
"Translated with the permission of Engr. Md.Asfak-Ur-Rahman, asfak-ur-rahman.blogspot.com”
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