arXiv：cs.AI· Danbinaerin Han, Wonil Kim, Seah Hong, Dongjoo Moon, Jaeok Lee, Jongpil Lee, Chaewon Kim, Juhan Nam·· 8 小时前
Gugak-VocalSet：韩国传统唱法 sigimsae 标注的多流派录音室级数据集
Gugak-VocalSet: A Multi-Genre Studio-Quality Dataset of Korean Traditional Singing with Sigimsae Annotations
AI 导读
Gugak-VocalSet 是首个公开的韩国传统唱法音频数据集，含 305 首曲目、24.5 小时无伴奏独唱录音，由 20 位专业歌手在录音室固定调性与速度下演唱。
正文
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 unaccompanied solo vocal recordings across 305 tracks of representative repertoire curated by the National Gugak Center, performed by 20 professional singers in a controlled studio environment with fixed key and tempo. In addition to genre, lyrics, and mood/timbre tags, the dataset provides a unified sigimsae ontology and approximately 68,000 segments (71,700 instances including multi-label) of audio-grounded sigimsae annotations; the ontology adopts a functional-position-based hierarchy designed for consistent application across genres, and 14 expert annotators specializing in Korean traditional music performed segment-level labeling accordingly. Baseline experiments on sigimsae classification and event detection show that domain-informed F0 representations remain competitive with, and on classification surpass, frozen probing of a general-purpose music foundation model, while pitch and spectral cues play complementary roles in event-level detection. Companion page: this https URL
| Subjects: | Sound (cs.SD); Artificial Intelligence (cs.AI); Databases (cs.DB); Digital Libraries (cs.DL) |
| Cite as: | arXiv:2610.15350 [cs.SD] |
| (or arXiv:2610.15350v1 [cs.SD] for this version) | |
| https://doi.org/10.48550/arXiv.2610.15350 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Danbinaerin Han [view email]
[v1]
Sun, 11 Oct 2026 05:14:13 UTC (2,590 KB)
来源：arXiv：cs.AI · arxiv.org