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New dataset released for Korean traditional singing with sigimsae annotations

Researchers have introduced Gugak-VocalSet, a new dataset featuring Korean traditional singing with detailed annotations of sigimsae, a system for vocal expressions. The dataset comprises 24.5 hours of unaccompanied solo vocal recordings from 305 tracks, performed by 20 professional singers. It includes genre, lyrics, and mood tags, along with approximately 68,000 segments annotated for sigimsae using a unified ontology. Initial experiments demonstrate that domain-informed F0 representations are competitive with general-purpose music foundation models for sigimsae classification. AI

RANK_REASON The cluster describes a new academic dataset release with annotations for a specific domain. [lever_c_demoted from research: ic=1 ai=1.0]

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New dataset released for Korean traditional singing with sigimsae annotations

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The cluster describes a new academic dataset release with annotations for a specific domain. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Danbinaerin Han, Wonil Kim, Seah Hong, Dongjoo Moon, Jaeok Lee, Jongpil Lee, Chaewon Kim, Juhan Nam ·

    Gugak-VocalSet: A Multi-Genre Studio-Quality Dataset of Korean Traditional Singing with Sigimsae Annotations

    arXiv:2610.15350v1 Announce Type: cross Abstract: We present Gugak-VocalSet, the first publicly available audio dataset for Korean traditional singing with dense annotations of sigimsae, a structured pitch contour system of vocal expressions. Gugak-VocalSet contains 24.5 hours of…