10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Automated Pronunciation Scoring Using Confidence Scoring and Landmark-Based SVM

Su-Youn Yoon (1), Mark Hasegawa-Johnson (1), Richard Sproat (2)

(1) University of Illinois at Urbana-Champaign, USA
(2) Oregon Health & Science University, USA

In this study, we present a pronunciation scoring method for second language learners of English (hereafter, L2 learners). This study presents a method using both confidence scoring and classifiers. Classifiers have an advantage over confidence scoring for specialization in the specific phonemes where L2 learners make frequent errors. Classifiers (Landmark-based Support Vector Machines) were trained in order to distinguish L2 phonemes from their frequent substitution patterns.

In this study, the method was evaluated on the specific English phonemes where L2 English learners make frequent errors. The results suggest that the automated pronunciation scoring method can be improved consistently by combining the two methods.

Full Paper

Bibliographic reference.  Yoon, Su-Youn / Hasegawa-Johnson, Mark / Sproat, Richard (2009): "Automated pronunciation scoring using confidence scoring and landmark-based SVM", In INTERSPEECH-2009, 1903-1906.