Paper: Discriminative Lexicon Adaptation for Improved Character Accuracy - A New Direction in Chinese Language Modeling

ACL ID P09-1085
Title Discriminative Lexicon Adaptation for Improved Character Accuracy - A New Direction in Chinese Language Modeling
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

While OOV is always a problem for most languages in ASR, in the Chinese case the problem can be avoided by utilizing char- acter n-grams and moderate performances can be obtained. However, character n- gram has its own limitation and proper addition of new words can increase the ASR performance. Here we propose a dis- criminativelexiconadaptationapproachfor improved character accuracy, which not only adds new words but also deletes some words from the current lexicon. Different from other lexicon adaptation approaches, we consider the acoustic features and make our lexicon adaptation criterion consistent with that in the decoding process. The pro- posed approach not only improves the ASR character accuracy but also significantly enhances the performance of a character- based spoken documen...