Human computer interaction using isolated-words speech recognition technology

This research paper aims to develop an isolated-word automatic speech recognition (IWASR) system based on Vector Quantization (VQ). This system receives, analyzes, searches and matches an input speech signal with the trained set of speech signals which are stored in the database/codebook, and retu...

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Main Authors:	Abu Shariah, Mohammad Abd-Alrahman Mahmoud, Ainon, Raja Noor, Zainuddin, Roziati, Khalifa, Othman Omran
Format:	Conference or Workshop Item
Language:	English
Published:	2007
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/5881/ http://irep.iium.edu.my/5881/ http://irep.iium.edu.my/5881/ http://irep.iium.edu.my/5881/1/04658569.pdf

id	iium-5881
recordtype	eprints
spelling	iium-58812011-11-21T22:36:51Z http://irep.iium.edu.my/5881/ Human computer interaction using isolated-words speech recognition technology Abu Shariah, Mohammad Abd-Alrahman Mahmoud Ainon, Raja Noor Zainuddin, Roziati Khalifa, Othman Omran T Technology (General) This research paper aims to develop an isolated-word automatic speech recognition (IWASR) system based on Vector Quantization (VQ). This system receives, analyzes, searches and matches an input speech signal with the trained set of speech signals which are stored in the database/codebook, and returns matching results to users. IWASR is meant to assist customers calling a university’s telephone operator to respond to their enquiries in a convenient way using their natural speech. Callers are assisted to select language, faculty and the staff name they wish to contact. To extract features from speech signals, Mel-Frequency Cepstral Coefficients (MFCC) algorithm was applied. Subsequently, Vector Quantization was used for all feature vectors generated from the MFCC. A codebook was resulted from training the VQ initial codebook and experimental results showed that the recognition rate has been improved with the increase of codebook size and showed that the codebook size of 81 feature vectors had a recognition rate exceeded 85%. 2007 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/5881/1/04658569.pdf Abu Shariah, Mohammad Abd-Alrahman Mahmoud and Ainon, Raja Noor and Zainuddin, Roziati and Khalifa, Othman Omran (2007) Human computer interaction using isolated-words speech recognition technology. In: 2007 International Conference on Intelligent & Advanced Systems (ICIAS) , 25-28 November, 2007, Kuala Lumpur Convention Centre. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4658569 doi:10.1109/ICIAS.2007.4658569
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Abu Shariah, Mohammad Abd-Alrahman Mahmoud Ainon, Raja Noor Zainuddin, Roziati Khalifa, Othman Omran Human computer interaction using isolated-words speech recognition technology
description	This research paper aims to develop an isolated-word automatic speech recognition (IWASR) system based on Vector Quantization (VQ). This system receives, analyzes, searches and matches an input speech signal with the trained set of speech signals which are stored in the database/codebook, and returns matching results to users. IWASR is meant to assist customers calling a university’s telephone operator to respond to their enquiries in a convenient way using their natural speech. Callers are assisted to select language, faculty and the staff name they wish to contact. To extract features from speech signals, Mel-Frequency Cepstral Coefficients (MFCC) algorithm was applied. Subsequently, Vector Quantization was used for all feature vectors generated from the MFCC. A codebook was resulted from training the VQ initial codebook and experimental results showed that the recognition rate has been improved with the increase of codebook size and showed that the codebook size of 81 feature vectors had a recognition rate exceeded 85%.
format	Conference or Workshop Item
author	Abu Shariah, Mohammad Abd-Alrahman Mahmoud Ainon, Raja Noor Zainuddin, Roziati Khalifa, Othman Omran
author_facet	Abu Shariah, Mohammad Abd-Alrahman Mahmoud Ainon, Raja Noor Zainuddin, Roziati Khalifa, Othman Omran
author_sort	Abu Shariah, Mohammad Abd-Alrahman Mahmoud
title	Human computer interaction using isolated-words speech recognition technology
title_short	Human computer interaction using isolated-words speech recognition technology
title_full	Human computer interaction using isolated-words speech recognition technology
title_fullStr	Human computer interaction using isolated-words speech recognition technology
title_full_unstemmed	Human computer interaction using isolated-words speech recognition technology
title_sort	human computer interaction using isolated-words speech recognition technology
publishDate	2007
url	http://irep.iium.edu.my/5881/ http://irep.iium.edu.my/5881/ http://irep.iium.edu.my/5881/ http://irep.iium.edu.my/5881/1/04658569.pdf
first_indexed	2023-09-18T20:14:41Z
last_indexed	2023-09-18T20:14:41Z
_version_	1777407708398354432

Human computer interaction using isolated-words speech recognition technology

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