Dynamic feature extraction by wavelet analysis
نویسندگان
چکیده
Phoneme recognition is a difficult task in speech recognition as it is variable in length and its acoustic properties change due to co-articulation and variation in dialects. The performance of the speech recognition system is heavily based on features extracted for the phonemes. The conventional technique of Short Time Fourier Transform (STFT) has a serious limitation in resolving the stop (plosive) sounds. This shortcoming can be overcome by using the multi-resolution capability of Wavelet Analysis. In this paper we perform a comparative study of Discrete Wavelet Transform (DWT) and Wavelet Packet (WP) for new dynamic features extraction of phonemes.
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TUFEKCI, z., and GOWDY, J.N.: ‘Feature extraction using discrete wavelet transform for speech recognition’. Proc. IEEE Southeastcon 2000, Nashville, USA, 2000, pp. 116-123 FAROOQ, o., and DATTA, s.: ‘Dynamic feature extraction by wavelet analysis’. Proc. 6th Int. Conf. Spoken Language Processing, Beijing, China, Oct. 2000, Vol. 4, pp. 696-699 CHANG, s., KWON, Y . , and YANG, S I . : ‘Speech fea...
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