Sixth International Conference on Spoken Language Processing
(ICSLP 2000)

Beijing, China
October 16-20, 2000

Prosodic Features for Automatic Text-Independent Evaluation of Degree of Nativeness for Language Learners

Carlos Teixeira (1,2), Horacio Franco (2), Elizabeth Shriberg (2), Kristin Precoda (2), Kemal Sönmez (2)

(1) IST-UTL/INESC, Lisbon, Portugal
(2) SRI International, Menlo Park, CA, USA

Predicting the degree of nativeness of a student 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. To achieve improved correlations between human and automatic nativeness scores, other aspects of speech should 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.

Full Paper

Bibliographic reference.  Teixeira, Carlos / Franco, Horacio / Shriberg, Elizabeth / Precoda, Kristin / Sönmez, Kemal (2000): "Prosodic features for automatic text-independent evaluation of degree of nativeness for language learners", In ICSLP-2000, vol.3, 187-190.