Abstract
This paper proposes prosodic unit based segmentation for prosody evaluation by using pitch accent detection and forced alignment techniques. Support VectorMachine (SVM) is used to evaluate the prosody of non-native English speakers without reference utterances. Experimental results show the superiority of prosodic unit segmentation over word segmentation in terms of classification accuracy and dimension of the feature vectors used by SVM.
| Original language | English |
|---|---|
| Pages (from-to) | 2143-2146 |
| Number of pages | 4 |
| Journal | IEICE Transactions on Information and Systems |
| Volume | E96-D |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - Sept 2013 |
| Externally published | Yes |
ASJC Scopus Subject Areas
- Software
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence
Keywords
- Pitch accent
- Prosodic unit
- Prosody evaluation
- Segmentation