Detecting Hands from Piano MIDI Data
| dc.contributor.author | Hadjakos, Aristotelis | |
| dc.contributor.author | Waloschek, Simon | |
| dc.contributor.author | Leemhuis, Alexander | |
| dc.date.accessioned | 2019-09-05T01:06:38Z | |
| dc.date.available | 2019-09-05T01:06:38Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | When a pianist is playing on a MIDI keyboard, the computer does not know with which hand a key was pressed. With the help of a Recurrent Neural Network (RNN), we assign played MIDI notes to one of the two hands. We compare our new approach with an existing heuristic algorithm and show that RNNs perform better. The solution is real-time capable and can be used via OSC from any programming environment. A non real-time capable variant provides slightly higher accuracy. Our solution can be used in music notation software to assign the left or right hand to the upper or lower staff automatically. Another application is live playing, where different synthesizer sounds can be mapped to the left and right hand. | en |
| dc.identifier.doi | 10.18420/muc2019-ws-578 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/25209 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Mensch und Computer 2019 - Workshopband | |
| dc.relation.ispartofseries | Mensch und Computer | |
| dc.subject | piano | |
| dc.subject | music | |
| dc.subject | datasets | |
| dc.subject | neural networks | |
| dc.title | Detecting Hands from Piano MIDI Data | en |
| dc.type | Text/Workshop Paper | |
| gi.citation.publisherPlace | Bonn | |
| gi.conference.date | 8.-11. September 2019 | |
| gi.conference.location | Hamburg | |
| gi.conference.sessiontitle | MCI-WS23: Innovative Computerbasierte Musikinterfaces (ICMI) | |
| gi.document.quality | digidoc |
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