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English digits speech recognition system based on Hidden Markov Models

Abushariah, Ahmad A. M. and Gunawan, Teddy Surya and Khalifa, Othman Omran and Abushariah, Mohammad Abd-Alrahman Mahmoud (2010) English digits speech recognition system based on Hidden Markov Models. In: International Conference on Computer and Communication Engineering ICCCE 2010, 11-13 May, 2010, Kuala Lumpur, Malaysia.

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Abstract

This paper aims to design and implement English digits speech recognition system using Matlab (GUI). This work was based on the Hidden Markov Model (HMM), which provides a highly reliable way for recognizing speech. The system is able to recognize the speech waveform by translating the speech waveform into a set of feature vectors using Mel Frequency Cepstral Coefficients (MFCC) technique This paper focuses on all English digits from (Zero through Nine), which is based on isolated words structure. Two modules were developed, namely the isolated words speech recognition and the continuous speech recognition. Both modules were tested in both clean and noisy environments and showed a successful recognition rates. In clean environment and isolated words speech recognition module, the multi-speaker mode achieved 99.5% whereas the speaker-independent mode achieved 79.5%. In clean environment and continuous speech recognition module, the multi-speaker mode achieved 72.5% whereas the speaker-independent mode achieved 56.25%. However in noisy environment and isolated words speech recognition module, the multi-speaker mode achieved 88% whereas the speaker-independent mode achieved 67%. In noisy environment and continuous speech recognition module, the multi-speaker mode achieved 82.5% whereas the speaker-independent mode achieved 76.67%. These recognition rates are relatively successful if compared to similar systems.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 5588/2328 (Proceedings of the International Conference on Computer and Communication Engineering (ICCCE),ISBN: 9781424462339)
Uncontrolled Keywords: English digits; Features extraction; Hidden Markov Models; Mel Frequency Cepstral Coefficients
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr Teddy Surya Gunawan
Date Deposited: 29 Sep 2011 04:51
Last Modified: 24 Nov 2011 14:00
URI: http://irep.iium.edu.my/id/eprint/2328

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