Pronunciation gestures based on articulatory feature extracted from Speech
| Project/Area Number |
24720254
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Foreign language education
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| Research Institution | Aichi Prefectural University (2013-2014)
Toyohashi University of Technology (2012) |
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Principal Investigator |
IRIBE Yurie 愛知県立大学, 情報科学部, 助教 (40397500)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | 発音訓練 / 外国語教育 / 調音運動 / 可視化 |
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| Outline of Final Research Achievements |
We describe computer-assisted pronunciation training (CAPT) through the visualization of the articulatory gestures from learner’s speech in this paper. Typical CAPT systems cannot indicate how the learner can correct his/her articulation. The proposed system enables the learner to study how to correct their pronunciation by comparing the wrongly pronounced gesture with a correctly pronounced gesture. In this system, a multi-layer neural network (MLN) is used to convert the learner’s speech into the coordinates for a vocal tract using Magnetic Resonance Imaging data. Then, an animation is generated using the values of the vocal tract coordinates. Moreover, we improved the animations by introducing an anchor-point for a phoneme to MLN training. The new system could even generate accurate CG animations from the English speech by Japanese people in the experiment.
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Report
(4 results)
Research Products
(25 results)
