2024
INTERSPEECH
INTERSPEECH 2024
CALL system using pitch-accent feature representations reflecting listeners’ subjective adequacy
Abstract
This paper presents a CALL system that implements a method for automatically and quantitatively evaluating the pitch accents of spoken words of Japanese learners in terms of how well they are accepted by native speakers.
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Interdisciplinary Bridge
— Interdisciplinary and Machine Learning
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Speech & Audio