Paper: Investigating Pitch Accent Recognition in Non-native Speech

ACL ID P09-2068
Title Investigating Pitch Accent Recognition in Non-native Speech
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2009
Authors

Acquisition of prosody, in addition to vo- cabulary and grammar, is essential for lan- guage learners. However, it has received less attention in instruction. To enable automatic identification and feedback on learners’ prosodic errors, we investigate automatic pitch accent labeling for non- native speech. We demonstrate that an acoustic-based context model can achieve accuracies over 79% on binary pitch ac- cent recognition when trained on within- group data. Furthermore, we demonstrate that good accuracies are achieved in cross- group training, where native and near- native training data result in no significant loss of accuracy on non-native test speech. These findings illustrate the potential for automatic feedback in computer-assisted prosody learning.