Lexicalized Phonotactic Word Segmentation

This paper presents a new unsupervised algorithm (WordEnds) for inferring word boundaries from transcribed adult conversations. Phone ngrams before and after observed pauses are used to bootstrap a simple discriminative model of boundary marking. This fast algorithm delivers high performance even on morphologically complex words in English and Arabic, and promising results on accurate phonetic transcriptions with extensive pronunciation variation. Expanding training data beyond the traditional miniature datasets pushes performance numbers well above those previously reported. This suggests that WordEnds is a viable model of child language acquisition and might be useful in speech understanding.

• Type: Conference
• Year: 2008
• Where: ACL
• Authors: Margaret M. Fleck
• Keywords: ACL 2008, Computational Linguistics, Datasets Pushes Performance, Fast Algorithm Delivers, Simple Discriminative Model