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arXiv · 2506.19315

JCAPT: A Joint Modeling Approach for CAPT

Tzu-Hsuan Yang·Yue-Yang He·Berlin Chen
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Abstract

Effective pronunciation feedback is critical in second language (L2) learning, for which computer-assisted pronunciation training (CAPT) systems often encompass two key tasks: automatic pronunciation assessment (APA) and mispronunciation detection and diagnosis (MDD). Recent work has shown that joint modeling of these two tasks can yield mutual benefits. Our unified framework leverages Mamba, a selective state space model (SSM), while integrating phonological features and think token strategies to jointly enhance interpretability and fine-grained temporal reasoning in APA and MDD. To our knowledge, this is the first study to combine phonological attribution, SSM-based modeling, and prompting in CAPT. A series of experiments conducted on the speechocean762 benchmark demonstrate that our model consistently outperforms prior methods, particularly on the MDD task.

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Tzu-Hsuan Yang, Yue-Yang He, Berlin Chen. 2025-06-24. JCAPT: A Joint Modeling Approach for CAPT. https://arxiv.org/abs/2506.19315

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