Transcrição automática de sons polifônicos de guitarra na notação de tablaturas utilizando classificação temporal conexionista
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Data
2024-09-23
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Universidade Federal de Goiás
Resumo
Automatic Guitar Transcription, a branch of Automatic Musical Transcription, is a task
with great applicability for musicians of fretted instruments such as the electric guitar
and acoustic guitar. Often, musicians on these instruments transcribe or read songs and
musical pieces in tablature format, a notation widely used for this type of instrument.
Despite its relevance, this annotation is still done manually, making it a very complex
process, even for experienced musicians. In this context, this work proposes the use of
artificial intelligence to develop models capable of performing the task of transcribing
polyphonic guitar sounds automatically. In particular, this work investigates the use of a
specific method called Connectionist Temporal Classification (CTC), an algorithm that
can be used to train sequence classification models without the need for alignment, a
fundamental aspect for training more robust models, as there are few openly available
datasets. Additionally, this work investigates multi-task learning for note prediction
alongside tablature prediction, achieving significant improvements over conventional
learning. Overall, the results indicate that the use of CTC is very promising for tablature
transcription, showing only a 14.28% relative decrease compared to the result obtained
with aligned data.
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Citação
GRIS, L. R. S. Transcrição Automática de Sons Polifônicos de Guitarra na Notação de Tablaturas Utilizando Classificação Temporal Conexionista. 2024. 81 f. Dissertação (Mestrado em Ciência da Computação) - Instituto de Informática, Universidade Federal de Goiás, Goiânia, 2024.