A holistic approach to polyphonic music transcription with neural networks

26 Oct 2019Miguel A. RománAntonio PertusaJorge Calvo-Zaragoza

We present a framework based on neural networks to extract music scores directly from polyphonic audio in an end-to-end fashion. Most previous Automatic Music Transcription (AMT) methods seek a piano-roll representation of the pitches, that can be further transformed into a score by incorporating tempo estimation, beat tracking, key estimation or rhythm quantization... (read more)

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