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
Format: Conference or Workshop Item
Language:English
Published: 2011
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/338/
http://eprints.utem.edu.my/id/eprint/338/1/SPECTRUM_ANALYSIS_OF_SPEECH_RECOGNITION_VIA.pdf
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author Ernawan, Ferda
Abu, Nur Azman
Herman, Nanna Suryana
author_facet Ernawan, Ferda
Abu, Nur Azman
Herman, Nanna Suryana
author_sort Ernawan, Ferda
building UTeM Institutional Repository
collection Online Access
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.
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institution Universiti Teknikal Malaysia Melaka
institution_category Local University
language English
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publishDate 2011
recordtype eprints
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spelling utem-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.
spellingShingle QA Mathematics
QP Physiology
Ernawan, Ferda
Abu, Nur Azman
Herman, Nanna Suryana
Spectrum analysis of speech recognition via discrete Tchebichef transform
title 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_short Spectrum analysis of speech recognition via discrete Tchebichef transform
title_sort spectrum analysis of speech recognition via discrete tchebichef transform
topic QA Mathematics
QP Physiology
url http://eprints.utem.edu.my/id/eprint/338/
http://eprints.utem.edu.my/id/eprint/338/1/SPECTRUM_ANALYSIS_OF_SPEECH_RECOGNITION_VIA.pdf