Audio-to-score alignment (A2SA) is a multimodal task consisting in the alignment of audio signals to music scores. Recent literature confirms the benefits of Automatic Music Transcription (AMT) for A2SA at the frame-level. In this work, we aim to elaborate on the exploitation of AMT Deep Learning (DL) models for achieving alignment at the note-level. We propose a method which benefits from HMM-based score-to-score alignment and AMT, showing a remarkable advancement beyond the state-of-the-art. We design a systematic procedure to take advantage of large datasets which do not offer an aligned score. Finally, we perform a thorough comparison and extensive tests on multiple datasets.

Audio-to-Score Alignment Using Deep Automatic Music Transcription / F. Simonetta, S. Ntalampiras, F. Avanzini - In: 2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP)[s.l] : IEEE, 2021. - ISBN 978-1-6654-3288-7. - pp. 1-6 (( Intervento presentato al 23. convegno IEEE International Workshop on Multimedia Signal Processing (IEEE MMSP) tenutosi a Tampere nel 2021 [10.1109/MMSP53017.2021.9733531].

Audio-to-Score Alignment Using Deep Automatic Music Transcription

F. Simonetta
Primo
;
S. Ntalampiras
Secondo
;
F. Avanzini
Ultimo
2021

Abstract

Audio-to-score alignment (A2SA) is a multimodal task consisting in the alignment of audio signals to music scores. Recent literature confirms the benefits of Automatic Music Transcription (AMT) for A2SA at the frame-level. In this work, we aim to elaborate on the exploitation of AMT Deep Learning (DL) models for achieving alignment at the note-level. We propose a method which benefits from HMM-based score-to-score alignment and AMT, showing a remarkable advancement beyond the state-of-the-art. We design a systematic procedure to take advantage of large datasets which do not offer an aligned score. Finally, we perform a thorough comparison and extensive tests on multiple datasets.
audio-to-score alignment; automatic-music-transcription; music information retrieval
Settore INF/01 - Informatica
Settore ING-INF/06 - Bioingegneria Elettronica e Informatica
Settore L-ART/07 - Musicologia e Storia della Musica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/945976
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