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Deep Composer Classification Using Symbolic Representation

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 نشر من قبل Jinho Lee
 تاريخ النشر 2020
  مجال البحث الهندسة المعلوماتية
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In this study, we train deep neural networks to classify composer on a symbolic domain. The model takes a two-channel two-dimensional input, i.e., onset and note activations of time-pitch representation, which is converted from MIDI recordings and performs a single-label classification. On the experiments conducted on MAESTRO dataset, we report an F1 value of 0.8333 for the classification of 13~classical composers.



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