Paper: A Ranking Approach to Stress Prediction for Letter-to-Phoneme Conversion

ACL ID P09-1014
Title A Ranking Approach to Stress Prediction for Letter-to-Phoneme Conversion
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

Correct stress placement is important in text-to-speech systems, in terms of both the overall accuracy and the naturalness of pronunciation. In this paper, we formu- late stress assignment as a sequence pre- diction problem. We represent words as sequences of substrings, and use the sub- strings as features in a Support Vector Ma- chine (SVM) ranker, which is trained to rank possible stress patterns. The rank- ing approach facilitates inclusion of arbi- trary features over both the input sequence and output stress pattern. Our system ad- vances the current state-of-the-art, predict- ing primary stress in English, German, and Dutch with up to 98% word accuracy on phonemes, and 96% on letters. The sys- tem is also highly accurate in predicting secondary stress. Finally, when applied in tande...