人工知能学会全国大会論文集
Online ISSN : 2758-7347
35th (2021)
セッションID: 3N1-IS-2d-04
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MIDI note embedding with fastText model
*Yingfeng FUYusuke TANIMURAHidemoto NAKADA
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Distributed word representation greatly promoted research in NLP. Same as languages, MIDI music is constructed in the way of sequence, with a determined alphabet of notes and events. We proposed a way of training MIDI note embedding with an adaption of Facebook's fastText model. We then evaluate the model by word similarity, word analogy, and a classification task. The result shows that the adopted fastText model generalizes well in MIDI data and it’s promising to be used on future downstream tasks.

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© 2021 The Japanese Society for Artificial Intelligence
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