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Robust classification of stop consonants using auditory-based speech processing
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221)
In this work, a feature-based system for the automatic classification of stop consonants, in speaker independent continuous speech, is reported. The system uses a new auditory-based speech processing frontend that is based on the biologically rooted property of average localized synchrony detection (ALSD). It incorporates new algorithms for the extraction and manipulation of the acoustic-phonetic features that proved, statistically, to be rich in their information content. The experiments aredoi:10.1109/icassp.2001.940772 dblp:conf/icassp/AliSM01 fatcat:3vjo77tmujdtba3s4ruit654fm