Title: Towards a "Primal Sketch" of Speech
Speaker: Hynek Hermansky, IDIAP Research Institute

Abstract:
Most of automatic speech recognizers attempt to find model of the 
utterance that would be most consistent with observed "data". The "data"
typically represent a transformation of sequence of short-term spectral
vectors, i.e. the sequence of spectral components of short (10-20 ms)
segments of speech signal. The talk discusses alternative representation
of acoustic signal based on likelihoods of (so far not well specified)
sound events and argues for its better consistency with current
knowledge of mammalian hearing system.