In Automatic Music Transcription, onset information is useful for correcting timing issues of multi-pitch estimation processes and obtain note-level representations of audio signals. Although this idea has been often used in transcription systems, it is still unclear to which degree its use is beneficial. We address this question by studying the influence of the accuracy of onset information in piano music transcription. Results indicate that note tracking results improve when the onset information provided is accurately estimated and properly included with the correct strategy. Additionally, results depict an important accuracy gap in note tracking when considering ground-truth onset information compared to using an automatic onset estimation algorithm, showing the need for more accurate onset detection methods for music transcription systems.

Authors: Valero-Mas, Jose J.; Benetos, Emmanouil; Iñesta, Jose M.
Affiliations: University of Alicante, Alicante, Spain; Queen Mary University of London, London, UK(See document for exact affiliation information.)
AES Conference: 2017 AES International Conference on Semantic Audio (June 2017)
Paper Number: P2-4
Publication Date: June 13, 2017
Subject: Semantic Audio

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