TRAPS - classifiers of temporal patterns

The work proposes a radically different set of features for ASR where TempoRAl Patterns of spectral energies are used in place of the conventional spectral patterns. The approach has several inherent advantages, among them robustness to stationary or slowly varying disturbances. 1. INTRODUCTION 1.1. Spectral features In 1665 Isaac Newton made the following observation: The filling of a very deepe flaggon with a constant streame of beere or water sounds yer vowells in this order w, u, !, o, a, e, i, y 8. What young Newton observed was the spectral resonance peak which enhanced the spectrum of the beer pouring sound and moved up in frequency as the deepe flaggon was filling up. Since then, attempts to find acoustic correlates of phonetic categories mostly followed Newtons lead and studied the spectrum of speech. Spectrum-based techniques form the basis of most feature extraction methods in current ASR. A problem with the spectrum of sound is that it can easily be modified by v...