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Research·arXiv cs.CL·

Deep Supervised Contrastive Learning of Pitch Contours for Robust Pitch Accent Classification in Seoul Korean

Illustration accompanying: Deep Supervised Contrastive Learning of Pitch Contours for Robust Pitch Accent Classification in Seoul Korean

Researchers introduce Dual-Glob, a supervised contrastive learning framework that maps continuous pitch contours to discrete tonal categories in Seoul Korean, validated on a new 10,093-phrase benchmark dataset. The approach captures holistic F0 patterns by enforcing consistency between clean and augmented speech views, addressing a longstanding challenge in intonational phonology.

MentionsDual-Glob · Seoul Korean · Autosegmental-Metrical model

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Deep Supervised Contrastive Learning of Pitch Contours for Robust Pitch Accent Classification in Seoul Korean · Modelwire