Masatake Dantsuji — accepted AI-conference papers

2018

Efficient Learning of Articulatory Models Based on Multi-Label Training and Label Correction for Pronunciation Learning

Richeng Duan, Tatsuya Kawahara, Masatake Dantsuji, Hiroaki Nanjo

ICASSP 2018accepted

Articulatory feedback is effective for computer-assisted pronunciation training (CAPT) systems. This paper investigates efficient model learning methods for providing articulatory information to language learners. We first propose an articulatory attribute modeling method based on a multi-label lear…

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2017

Effective articulatory modeling for pronunciation error detection of L2 learner without non-native training data

Richeng Duan, Tatsuya Kawahara, Masatake Dantsuji, Jinsong Zhang

ICASSP 2017accepted

For effective articulatory feedback in computer-assisted pronunciation training (CAPT) systems, we address effective articulatory models of second language (L2) learners' speech without using such data, which is difficult to collect and annotate in a large scale. Context-dependent articulatory attri…

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