Abstract
Our goal is to develop a voice-interactive CALL system which enables language learners to practice words, phrases, and grammars interactively. Such a system must be able to recognize learner's utterances correctly. To enable the recognition of utterances containing grammatical mistakes, we used an n-gram language model trained from generated text. The proposed model achieved recognition performance similar to that of a language model based on a finite-state automaton and manual error rules. We then introduced two error correction techniques to improve recognition performance. One method used the Levenshtein distance between the target sentence and the recognized sentence. The other method used an error-corrective model based on POS n-gram features. The experimental results showed that both methods were able to improve recognition performance.
| Original language | English |
|---|---|
| Pages (from-to) | 2819-2822 |
| Number of pages | 4 |
| Journal | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH |
| Publication status | Published - 2008 |
| Event | INTERSPEECH 2008 - 9th Annual Conference of the International Speech Communication Association - Brisbane, QLD, Australia Duration: 2008 Sept 22 → 2008 Sept 26 |
Keywords
- CALL system
- Error-corrective language model
- Grammatical errors
- Speech recognition
- Text generation