Finding Acoustic Regularities in Speech: Applications to Phonetic Recognition

Abstract
Phonetic recognition can be viewed as a process through which the acoustic signal is mapped to a set of phonological units used to represent a lexicon. Traditionally, researchers often prescribe an intermediate, phonetic description to account for coarticulation. This thesis presents an alternative approach whereby this phonetic-level description is bypassed in favor of directly relating the acoustic realization to the underlying phonemic forms. In this approach, the speech signal is transformed into a set of segments which are described completely in a acoustic terms. Next, these acoustic segments are related to the phonemes by a grammar which is determined using automated procedures operating on a set of training data. Thus important acoustic regularities that describes contextual variations are discovered without the need to specify a set of preconceived units such as allophones. The viability of this approach depends critically on the ability to detect important acoustic landmarks in the speech signal, and to describe these events in terms of an inventory of labels that captures the regularity of phonetic variations. Keywords: Acoustic segmentation; Acoustic classification.

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