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Fake Song Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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데이터셋

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SONICS

SONICS is a large-scale dataset comprising 97,164 songs — 48,090 real songs from YouTube and 49,074 fake songs from Suno & Udio — designed for synthetic song detection (SSD), also known as fake song detection (FSD). It addresses several limitations of existing datasets, such as the lack of end-to-end fake songs, limited diversity in music-lyrics, and insufficient long-duration songs. The average length of the songs in SONICS is 176 seconds, which enables the capture of long-context relationships. Moreover, SONICS provides open access to generated fake songs and is divided into 66,709 songs for training, 26,015 songs for testing, and 4,440 songs for validation. Additionally, the inclusion of song lyrics in SONICS dataset paves the way for future research in this field.

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.