The efficient discrete tchebichef transform for spectrum analysis of speech recognition
Speech recognition is still a growing field of importance. The growth in computing power will open its strong potentials for full use in the near future. Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) has been a traditional technique to analyze frequ...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SPIE
2011
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| Online Access: | http://eprints.utem.edu.my/id/eprint/336/ http://eprints.utem.edu.my/id/eprint/336/1/01-C00146-R001.pdf |
| _version_ | 1848886929553096704 |
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| author | Ernawan, Ferda Abu, Nor Azman |
| author_facet | Ernawan, Ferda Abu, Nor Azman |
| author_sort | Ernawan, Ferda |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | Speech recognition is still a growing field of importance. The growth in computing power will open its strong potentials for full use in the near future. Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) has been a traditional technique to analyze frequency spectrum of the signals in speech recognition. FFT is computationally complex especially with imaginary numbers. The Discrete Tchebichef Transform (DTT) is
proposed instead of the popular FFT. DTT has lower computational complexity and it does not require complex transform dealing with imaginary numbers. This paper proposes a novel approach based on 256 discrete orthonormal Tchebichef polynomials as efficient technique to analyze a vowel and a consonant in spectral frequency of speech recognition. The comparison between 1024 discrete
orthonormal Tchebichef transform and 256 discrete orthonormal Tchebichef transform has been done. The preliminary experimental results show that 256 DTT has the potential to be more efficient to transform time domain into frequency domain for speech recognition. 256 DTT produces simpler output than 1024 DTT in frequency spectrum. At the same time, 256 Discrete Tchebichef Transform can produce concurrently four formants F1, F2, F3 and F4. |
| first_indexed | 2025-11-15T19:46:18Z |
| format | Article |
| id | utem-336 |
| institution | Universiti Teknikal Malaysia Melaka |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:46:18Z |
| publishDate | 2011 |
| publisher | SPIE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utem-3362023-07-20T12:18:57Z http://eprints.utem.edu.my/id/eprint/336/ The efficient discrete tchebichef transform for spectrum analysis of speech recognition Ernawan, Ferda Abu, Nor Azman QA Mathematics Speech recognition is still a growing field of importance. The growth in computing power will open its strong potentials for full use in the near future. Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) has been a traditional technique to analyze frequency spectrum of the signals in speech recognition. FFT is computationally complex especially with imaginary numbers. The Discrete Tchebichef Transform (DTT) is proposed instead of the popular FFT. DTT has lower computational complexity and it does not require complex transform dealing with imaginary numbers. This paper proposes a novel approach based on 256 discrete orthonormal Tchebichef polynomials as efficient technique to analyze a vowel and a consonant in spectral frequency of speech recognition. The comparison between 1024 discrete orthonormal Tchebichef transform and 256 discrete orthonormal Tchebichef transform has been done. The preliminary experimental results show that 256 DTT has the potential to be more efficient to transform time domain into frequency domain for speech recognition. 256 DTT produces simpler output than 1024 DTT in frequency spectrum. At the same time, 256 Discrete Tchebichef Transform can produce concurrently four formants F1, F2, F3 and F4. SPIE 2011-04-01 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/336/1/01-C00146-R001.pdf Ernawan, Ferda and Abu, Nor Azman (2011) The efficient discrete tchebichef transform for spectrum analysis of speech recognition. International Journal of Machine Learning and Computing, 1 (1). 01-06. ISSN 0277-786X http://www.ijmlc.org/papers/01-C00146-R001.pdf 10.1117/12.2010642 |
| spellingShingle | QA Mathematics Ernawan, Ferda Abu, Nor Azman The efficient discrete tchebichef transform for spectrum analysis of speech recognition |
| title | The efficient discrete tchebichef transform for spectrum analysis of speech recognition |
| title_full | The efficient discrete tchebichef transform for spectrum analysis of speech recognition |
| title_fullStr | The efficient discrete tchebichef transform for spectrum analysis of speech recognition |
| title_full_unstemmed | The efficient discrete tchebichef transform for spectrum analysis of speech recognition |
| title_short | The efficient discrete tchebichef transform for spectrum analysis of speech recognition |
| title_sort | efficient discrete tchebichef transform for spectrum analysis of speech recognition |
| topic | QA Mathematics |
| url | http://eprints.utem.edu.my/id/eprint/336/ http://eprints.utem.edu.my/id/eprint/336/ http://eprints.utem.edu.my/id/eprint/336/ http://eprints.utem.edu.my/id/eprint/336/1/01-C00146-R001.pdf |