YM2413-MDB: A Multi-Instrumental FM Video Game Music Dataset with Emotion Annotations
Existing multi-instrumental datasets tend to be biased toward pop and classical music. In addition, they generally lack high-level annotations such as emotion tags. In this paper, we propose YM2413-MDB, an 80s FM video game music dataset with multi-label emotion annotations. It includes 669 audio an...
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14-11-2022
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| Abstract | Existing multi-instrumental datasets tend to be biased toward pop and
classical music. In addition, they generally lack high-level annotations such
as emotion tags. In this paper, we propose YM2413-MDB, an 80s FM video game
music dataset with multi-label emotion annotations. It includes 669 audio and
MIDI files of music from Sega and MSX PC games in the 80s using YM2413, a
programmable sound generator based on FM. The collected game music is arranged
with a subset of 15 monophonic instruments and one drum instrument. They were
converted from binary commands of the YM2413 sound chip. Each song was labeled
with 19 emotion tags by two annotators and validated by three verifiers to
obtain refined tags. We provide the baseline models and results for emotion
recognition and emotion-conditioned symbolic music generation using YM2413-MDB. |
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| AbstractList | Existing multi-instrumental datasets tend to be biased toward pop and
classical music. In addition, they generally lack high-level annotations such
as emotion tags. In this paper, we propose YM2413-MDB, an 80s FM video game
music dataset with multi-label emotion annotations. It includes 669 audio and
MIDI files of music from Sega and MSX PC games in the 80s using YM2413, a
programmable sound generator based on FM. The collected game music is arranged
with a subset of 15 monophonic instruments and one drum instrument. They were
converted from binary commands of the YM2413 sound chip. Each song was labeled
with 19 emotion tags by two annotators and validated by three verifiers to
obtain refined tags. We provide the baseline models and results for emotion
recognition and emotion-conditioned symbolic music generation using YM2413-MDB. |
| Author | Chung, Yoonjin Nam, Juhan Choi, Eunjin Jeon, JongIk Kwon, Taegyun Lee, Seolhee |
| Author_xml | – sequence: 1 givenname: Eunjin surname: Choi fullname: Choi, Eunjin – sequence: 2 givenname: Yoonjin surname: Chung fullname: Chung, Yoonjin – sequence: 3 givenname: Seolhee surname: Lee fullname: Lee, Seolhee – sequence: 4 givenname: JongIk surname: Jeon fullname: Jeon, JongIk – sequence: 5 givenname: Taegyun surname: Kwon fullname: Kwon, Taegyun – sequence: 6 givenname: Juhan surname: Nam fullname: Nam, Juhan |
| BackLink | https://doi.org/10.48550/arXiv.2211.07131$$DView paper in arXiv |
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| Snippet | Existing multi-instrumental datasets tend to be biased toward pop and
classical music. In addition, they generally lack high-level annotations such
as emotion... |
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| SubjectTerms | Computer Science - Learning Computer Science - Multimedia Computer Science - Sound |
| Title | YM2413-MDB: A Multi-Instrumental FM Video Game Music Dataset with Emotion Annotations |
| URI | https://arxiv.org/abs/2211.07131 |
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