Degree Project

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The project compares the wavelet and cepstrum transforms for recognizing plosive and vocalic phonemes, using energy level coefficients for wavelet and the 14 first coefficients but the first for cepst$ systems.  The chosen phonemes were /p/, /t/, /e/, taken from a similar number of sample windows from a database of 93 phrases pronounced by a single speaker.  Wavelet and cepstrum had a similar performance for recognizing plosive phonemes.  For vocalic phonemes cepstrum had definitively better results.