| Autor: |
Yuto Ozaki, McBride, John, Benetos, Emmanouil, Pfordresher, Peter Q., Six, Joren, Tierney, Adam T., Proutskova, Polina, Sakai, Emi, Kondo, Haruka, Fukatsu, Haruno, Shinya Fujii, Savage, Patrick E. |
| Předmět: |
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| Zdroj: |
International Society for Music Information Retrieval Conference Proceedings; 2021, p500-508, 9p |
| Abstrakt: |
Cross-cultural musical analysis requires standardized symbolic representation of sounds such as score notation. However, transcription into notation is usually conducted manually by ear, which is time-consuming and subjective. Our aim is to evaluate the reliability of existing methods for transcribing songs from diverse societies. We had 3 experts independently transcribe a sample of 32 excerpts of traditional monophonic songs from around the world (half a cappella, half with instrumental accompaniment). 16 songs also had pre-existing transcriptions created by 3 different experts. We compared these human transcriptions against one another and against 10 automatic music transcription algorithms. We found that human transcriptions can be sufficiently reliable (~90% agreement, K ~.7), but current automated methods are not (<60% agreement, K <.4). No automated method clearly outperformed others, in contrast to our predictions. These results suggest that improving automated methods for cross-cultural music transcription is critical for diversifying MIR. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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