Learning structural models of subword units through grammatical inference techniques

Abstract
The authors propose obtaining the structure of phonetic units from training samples of speech automatically by using two specific grammatical inference (GI) algorithms: the error correcting GI algorithm and the morphic generator GI (MGGI) methodology. They describe the adequacy of the properties and capabilities of both methods for the modeling of subword units of speech (such as phonemes). They also report preliminary results obtained in their application to a continuous speech recognition, task. The results obtained with the semicontinuous MGGI methodology are shown to be very encouraging and can be improved with the use of some phonological grammar.

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