| Project/Area Number |
16300260
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Educational technology
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| Research Institution | Tohoku University |
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Principal Investigator |
ITO Akinori Tohoku University, Graduate School of Engineering, Associate Processor (70232428)
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| Co-Investigator(Kenkyū-buntansha) |
SUZUKI Motoyuki Graduate School of Engineering, 大学院・工学研究科, Assistant Professor (30282015)
MAKINO Shozo Graduate School of Engineering, 大学院・工学研究科, Professor (00089806)
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| Project Period (FY) |
2004 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥7,820,000 (Direct Cost: ¥7,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2007: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2006: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 2005: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 2004: ¥3,200,000 (Direct Cost: ¥3,200,000)
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| Keywords | Language learning system / Pronunciation evaluation / Prosody evaluation / Interactive CALL system / Speaker adaptation / Grammatical error model / Intonation / Rhythm / 決定木 / n-gram / 誤り訂正モデル / 発音誤り検出 / 音素環境 / 機械学習 / 文法誤り検出 / SSTコーパス / CALLシステム / 音声認識 / 音素モデル / 話者適応学習 / 外国語学習 / MLLR法 / VFS法 / データベース |
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| Research Abstract |
1. Improvement of Pronunciation Evaluation
We developed a method to detect pronunciation mistakes made by a foreign language learner by applying a speech recognition technology. We focused on the following two targets: learning of English by Japanese native speakers and learning of Japanese by Korean native speakers. To improve the accuracy of detection of mispronunciations, we developed a bilingual speaker adaptation method to adapt both of English and Japanese HMMs to the learner. To solve a problem that the strictness of the detection of mispronunciations depends on the linguistic context of the pronunciation, we developed a method of detecting mispronunciations using a decision tree, which gave a detection accuracy of more than 90% on English utterances made by Japanese native speakers.
2. Evaluation of Intonation and Rhythm
In addition to the detection of mispronunciations, we developed methods to evaluate intonation and rhythm of the English utterances. We found that the log F0, log power and their derivatives were good features for the evaluation of intonation. To adjust the strictness of intonation evaluation from word to word, we introduced a method to estimate the word importance factors using a decision tree. We also found that a word duration ratio was a good feature for rhythm evaluation.
3. Development of an interactive CALL system
We developed a method of detecting grammatical errors from utterances of a learner for the application to an interactive CALL system that enables for a learner to learn a foreign language through dialogues with a computer. As for the learning of Japanese, we developed a method to recognize the learner's speech using a finite state automaton to which grammatical error rules were applied. As for the learning of English, we developed a method to use an n-gram language model trained from a corpus that was automatically generated using the grammatical error rules.
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