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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| 主要な著者: | , , |
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| フォーマット: | Conference or Workshop Item |
| 言語: | English |
| 出版事項: |
2011
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| 主題: | |
| オンライン･アクセス: | 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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| 要約: | 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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