Bangla User Adaptive Word Speech Recognition: Approaches and Comparisons

Adnan Firoze, Md Shamsul Arifin and Rashedur M. Rahman
Additional contact information
Adnan Firoze: Department of Electrical Engineering and Computer Science, North South University, Dhaka, Bangladesh
Md Shamsul Arifin: Department of Electrical Engineering and Computer Science, North South University, Dhaka, Bangladesh
Rashedur M. Rahman: Department of Electrical Engineering and Computer Science, North South University, Dhaka, Bangladesh

International Journal of Fuzzy System Applications (IJFSA), 2013, vol. 3, issue 3, 1-36

Abstract: The paper presents Bangla word speech recognition using two novel approaches with a comprehensive analysis. The first approach is based on spectral analysis and fuzzy logic and the second one uses Mel-Frequency Cepstral Coefficients (MFCC) analysis and feed-forward back-propagation neural networks. As human speech is imprecise and ambiguous, fuzzy logic – the base of which is indeed linguistic ambiguity, could serve as a precise tool for analyzing and recognizing human speech. The authors’ systems revolve around the visual representations of voiced signals – the Fourier energy spectrum and the MFCC. The essences of a Fourier energy spectrum and the MFCC are matrices that include information about properties of a sound by storing energy and frequency in discrete time. The decision making process of their systems is based on fuzzy logic and neural networks. Experimental results demonstrate that their fuzzy logic based system is 86% accurate whereas the Artificial Neural Networks (ANN) based system is 90% accurate compared to a commercial Hidden Markov Model (HMM) based speech recognizer that shows 73% accuracy on an average. Moreover, the authors’ research derives that, even though ANN gives a better recognition accuracy than the fuzzy logic based system, the fuzzy logic based system is more accurate when it comes to “more difficult” or “polysyllabic” words. In terms of runtime performance, the fuzzy logic based system outperforms the ANN based Bangla speech recognition system.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/ijfsa.2013070101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jfsa00:v:3:y:2013:i:3:p:1-36

Access Statistics for this article

International Journal of Fuzzy System Applications (IJFSA) is currently edited by Deng-Feng Li

More articles in International Journal of Fuzzy System Applications (IJFSA) from IGI Global
Bibliographic data for series maintained by Journal Editor ().