Improvement Of Animated Articulatory Gesture Extracted From Speech For Pronunciation Training

Computer-assisted pronunciation training (CAPT) was introduced for language education in recent years. CAPT scores the learner's pronunciation quality and points out wrong phonemes by using speech recognition technology. However, although the learner can thus realize that his/her speech is different from the teacher's, the learner still cannot control the articulation organs to pronounce correctly. The learner cannot understand how to correct the wrong articulatory gestures precisely. We indicate these differences by visualizing a learner's wrong pronunciation movements and the correct pronunciation movements with CG animation. We propose a system for generating animated pronunciation by estimating a learner's pronunciation movements from his/her speech automatically. The proposed system maps speech to coordinate values that are needed to generate the animations by using multilayer perceptron neural networks (MLP). We use MRI data to generate smooth animated pronunciations. Additionally, we verify whether the vocal tract area and articulatory features are suitable as characteristics of pronunciation movement through experimental evaluation.