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Title: Wavelet-based techniques for speech recognition
Author: Farooq, Omar
ISNI:       0000 0001 2448 3818
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2002
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In this thesis, new wavelet-based techniques have been developed for the extraction of features from speech signals for the purpose of automatic speech recognition (ASR). One of the advantages of the wavelet transform over the short time Fourier transform (STFT) is its capability to process non-stationary signals. Since speech signals are not strictly stationary the wavelet transform is a better choice for time-frequency transformation of these signals. In addition it has compactly supported basis functions, thereby reducing the amount of computation as opposed to STFT where an overlapping window is needed.
Supervisor: Not available Sponsor: Commonwealth Commission
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Phoneme recognition