Prosodic features for automatic text-independent evaluation of degree of nativeness for language learners
Carlos Teixeira, Horacio Franco, Elizabeth E. Shriberg, Kristin Precoda, Kemal Sönmez · 2000
Predicting the degree of nativeness of a student's utterance is an important issue in computer-aided language learning. This task has been addressed by many studies focusing on the segmental assessment of the speech signal. Toachieve improved correlations between human and automatic nativeness scores, other aspects of speechshould also be considered, such as prosody. The goal of this study is to evaluate the use of prosodic information to help predict the degree of nativeness of pronunciation, independent of the text. A supervised strategy based on human grades is used in an attempt to select promising features for this task. Preliminary results show improvements in the correlation between human and automatic scores.