While dynamics is an important characteristic in music performance, it has been rarely researched in automatic music transcription. We propose a method to estimate individual note intensities from a piano recording given pre-aligned score data of the recording. To this end, we use non-negative matrix factorization in a score-informed setting, where the basis vectors and weights are constrained to estimate harmonic note spectra and corresponding intensities, respectively. We examine various choices in the learning process including the use of synthesized note scale for initialization, type of spectrum, and temporal constraint. We evaluate our method using Saarland Music Data and estimate note intensities in MIDI velocity. The results show that the proposed method makes an improvement compare to previous work.
Jeong, Dasaem; Nam, Juhan
Affiliation: Korea Advanced Institute of Science and Technology, Dajeon, Korea
AES Conference: 2017 AES International Conference on Semantic Audio (June 2017)
Paper Number: 4-1
Publication Date: June 13, 2017
Subject: Automatic Music Transcription
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