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[Abstract] In this project, we tackle the problem of predicting the next note in a monophonic musical
piece. We choose a symbolic representation and extract it from digital sheet music. The problem
is approached as four separate tasks, each of them corresponding to a specific property of
the musical note. For each task, we compare the performance of both single and multi-output
deep learning algorithms. Despite the severe class imbalance in our dataset, our models
manage to generate balanced predictions for the four features.[Resumo] Neste proxecto tratamos o problema de predicir a seguinte nota nunha peza musical monofónica.
Escollemos unha representación simbólica e extraémola dun conxunto de partituras
dixitais. Afrontamos o problema como catro tarefas de predicción de propiedades inherentes
á nota musical. Para cada tarefa, comparamos o rendemento de algoritmos de aprendizaxe
profundo dunha e varias saídas. Aínda que o conxunto de datos está moi descompensado, os
nosos modelos son capaces de xerar predicións equilibradas nos catro problemas.Traballo fin de grao. Enxeñaría Informática. Curso 2021/202
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