Modelling Pronunciation in Discourse Context
Per-Anders Jande · 2009
This paper describes a method for modelling phone-level pronunciation in discourse context. Spoken language is annotated with linguistic and related information in several layers. The annotation serves as a description of the discourse context and is used as training data for decision tree model induction. In a cross validation experiment, the decision tree pronunciation models are shown to produce a phone error rate of 8.1 % when trained on all available data. This is an improvement by 60.2 % compared to using a phoneme string compiled from lexicon transcriptions for estimating phone-level pronunciation and an improvement by 42.6 % compared to using decision tree models trained on phoneme layer attributes only. 1 Introduction and