M. Ostendorf,
``Incorporating linguistic theories of phonological variation into speech recognition models,''
Royal Society Phil. Trans., to appear.

This paper describes the use of distinctive linguistic features to represent acoustic variability of words for speech recognition. Focusing on conventional HMM technology, we review implicit use of linguistic features as questions in decision tree design for both coarticulation and pronunciation modeling and describe possibilities for more explicit use. The importance of conditioning on (hierarchical) syllable and prosodic structure is discussed, and the problem of modeling relative timing of feature-dependent acoustic cues is raised as a key limitation of current models.

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