Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1903-1906 |
| Number of pages | 4 |
| Journal | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH |
| State | Published - 2009 |
| Event | 10th Annual Conference of the International Speech Communication Association, INTERSPEECH 2009 - Brighton, United Kingdom Duration: Sep 6 2009 → Sep 10 2009 |
Keywords
- Confidence score
- Landmark Support Vector Machine
- Speech recognition
ASJC Scopus subject areas
- Human-Computer Interaction
- Signal Processing
- Software
- Sensory Systems