Welcome to the UPF Digital Repository

Note level midi velocity estimation for piano performance

Show simple item record

dc.contributor.author Kim, Hyon
dc.contributor.author Miron, Marius
dc.contributor.author Serra, Xavier
dc.date.accessioned 2023-01-16T17:08:54Z
dc.date.available 2023-01-16T17:08:54Z
dc.date.issued 2023-01-16
dc.identifier.uri http://hdl.handle.net/10230/55285
dc.description.abstract Piano is one of the most popular music instruments. During the piano performance, loudness is an important factor for expressiveness, alongside tempo, changes in dynamics play with expectation, convey various emotions, and render expressiveness. Due to the polyphonic characteristics and with the goal of better analysing the expressiveness of performance of piano with multiple notes playing simultaneously, it is more useful to find loudness for each note than looking at accumulated loudness for a single time frame. Most of the research in this topic uses Non-negative Matrix Factorization (NMF) techniques to find note level loudness. In contrast, we propose to use Deep Neural Networks (DNNs) conditioned with score information to estimate the loudness based on MIDI velocity for each note performed by piano players. To our best knowledge, this is a novel research for note level MIDI velocity estimation by a DNN model in end to end fashion having FiLM conditioning.
dc.description.sponsorship This research was carried out under the project Musical AI - PID2019- 111403GB-I00/AEI/10.13039/501100011033, funded by the Spanish Ministerio de Ciencia e Innovación and the Agencia Estatal de Investigación.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.rights © H. Kim, M. Miron, and X. Serra. Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Attribution: H. Kim, M. Miron, and X. Serra, “Note level MIDI velocity estimation for piano performance”, in Extended Abstracts for the LateBreaking Demo Session of the 23rd Int. Society for Music Information Retrieval Conf., Bengaluru, India, 2022.
dc.rights.uri https://creativecommons.org/licenses/by/4.0
dc.title Note level midi velocity estimation for piano performance
dc.type info:eu-repo/semantics/preprint
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-111403GB-I00
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion


This item appears in the following Collection(s)

Show simple item record

Search DSpace

Advanced Search


My Account


In collaboration with Compliant to Partaking