Spectrum analysis of speech recognition via discrete Tchebichef transform

Speech recognition is still a growing field. It carries strong potential in the near future as computing power grows. Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) is the traditional technique to analyze frequency spectrum of the signal in speech re...

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Main Authors: Ernawan, Ferda, Abu, Nur Azman, Herman, Nanna Suryana
格式: Conference or Workshop Item
語言:English
出版: 2011
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spelling my.utem.eprints.3382023-07-20T12:25:49Z http://eprints.utem.edu.my/id/eprint/338/ Spectrum analysis of speech recognition via discrete Tchebichef transform Ernawan, Ferda Abu, Nur Azman Herman, Nanna Suryana QA Mathematics QP Physiology Speech recognition is still a growing field. It carries strong potential in the near future as computing power grows. Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) is the traditional technique to analyze frequency spectrum of the signal in speech recognition. Speech recognition operation requires heavy computation due to large samples per window. In addition, FFT consists of complex field computing. This paper proposes an approach based on discrete orthonormal Tchebichef polynomials to analyze a vowel and a consonant in spectral frequency for speech recognition. The Discrete Tchebichef Transform (DTT) is used instead of popular FFT. The preliminary experimental results show that DTT has the potential to be a simpler and faster transformation for speech recognition. 2011-10-01 Conference or Workshop Item PeerReviewed text en http://eprints.utem.edu.my/id/eprint/338/1/SPECTRUM_ANALYSIS_OF_SPEECH_RECOGNITION_VIA.pdf Ernawan, Ferda and Abu, Nur Azman and Herman, Nanna Suryana (2011) Spectrum analysis of speech recognition via discrete Tchebichef transform. In: International Conference on Graphic and Image Processing 2011.
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic QA Mathematics
QP Physiology
spellingShingle QA Mathematics
QP Physiology
Ernawan, Ferda
Abu, Nur Azman
Herman, Nanna Suryana
Spectrum analysis of speech recognition via discrete Tchebichef transform
description Speech recognition is still a growing field. It carries strong potential in the near future as computing power grows. Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) is the traditional technique to analyze frequency spectrum of the signal in speech recognition. Speech recognition operation requires heavy computation due to large samples per window. In addition, FFT consists of complex field computing. This paper proposes an approach based on discrete orthonormal Tchebichef polynomials to analyze a vowel and a consonant in spectral frequency for speech recognition. The Discrete Tchebichef Transform (DTT) is used instead of popular FFT. The preliminary experimental results show that DTT has the potential to be a simpler and faster transformation for speech recognition.
format Conference or Workshop Item
author Ernawan, Ferda
Abu, Nur Azman
Herman, Nanna Suryana
author_facet Ernawan, Ferda
Abu, Nur Azman
Herman, Nanna Suryana
author_sort Ernawan, Ferda
title Spectrum analysis of speech recognition via discrete Tchebichef transform
title_short Spectrum analysis of speech recognition via discrete Tchebichef transform
title_full Spectrum analysis of speech recognition via discrete Tchebichef transform
title_fullStr Spectrum analysis of speech recognition via discrete Tchebichef transform
title_full_unstemmed Spectrum analysis of speech recognition via discrete Tchebichef transform
title_sort spectrum analysis of speech recognition via discrete tchebichef transform
publishDate 2011
url http://eprints.utem.edu.my/id/eprint/338/1/SPECTRUM_ANALYSIS_OF_SPEECH_RECOGNITION_VIA.pdf
http://eprints.utem.edu.my/id/eprint/338/
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score 13.251813