Pronunciation variation modeling for ASR : large improvements are possible but small ones are likely to achieve
Qian Yang, J.-P. Martens, P.-J Ghesquière, Dirk Van Compernolle · Ghent University Academic Bibliography (Ghent University) · 2002
In this paper a previously proposed method for the automatic construction of a lexicon with pronunciation variants for ASR is further developed and evaluated. The basic idea is to transform a lexicon of canonical forms by means of rewrite rules that are learned automatically on a training corpus of orthographically transcribed utterances. The method is evaluated on the TIMIT corpus, using a speech recognizer incorporating context-independent HMMs and a bigram language model. It appears that reductions of the word error rate of up to 35 % are possible to achieve. However, it also appears that it is more likely to obtain much lower gains.