Current-generation automatic speech recognition (ASR) systems model spoken discourse as a quasi-linear sequence of words and phones. Because it is unusual for every phone within a word to be pronounced in a standard ("canonical") way, ASR systems often depend on a multi-pronunciation lexicon to match an acoustic sequence with a lexical unit. Since there are, in practice, many different ways for a word to be pronounced, this standard approach adds a layer of complexity and ambiguity to the decoding process which, if simplified, could potentially improve recognition performance. Systematic analysis of pronunciation variation in a corpus of spontaneous English discourse (Switchboard) demonstrates that the variation observed is more systematic at the level of the syllable than at the phonetic-segment level. Thus, syllabic onsets are realized in canonical form far more frequently than either coda or nuclear constituents. Prosodic prominence and lexical stress also appear to play an important role in pronunciation variation. The governing mechanism is likely to involve the informational valence associated with syllabic and lexical elements, and for this reason pronunciation variation offers a potential window onto the mechanisms responsible for the production and understanding of spoken language. (C) 1999 Elsevier Science B.V. All rights reserved.
