Discrete word recognition using energy-time profiles

Abstract
A novel isolated-word recognition system for monosyllabic tonal languages is proposed which depends on the energy-time profiles (ETP) of the utterances at different frequency bands. Training procedures, together with the classification strategy will be discussed. A mean accuracy of 97-99% was achieved for speaker-dependent recognition over the ten Cantonese digits.

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