Using Dutch phonological rules to model pronunciation variation in ASR

Abstract

In this paper, we describe how the performance of a continuous speech recognizer for Dutch has been improved by modeling within-word and cross-word pronunciation variation. Within-word variants were automatically generated by applying five phonological rules to the words in the lexicon. Cross-word pronunciation variation was modeled by adding multi-words and their variants to the lexicon. The best results were obtained when the cross-word method was combined with the within-word method: a relative improvement of 8.8% in the WER was found compared to baseline system performance. We also describe an error analysis that was carried out to investigate whether rules in isolation can predict the performance of rules in combination.