Figure 1
Chain of musical communication from composer to listener. The dotted box disappears for performances that are not recorded.
Figure 2
Variations in two different performances of Frédéric Chopin’s Fantasie in F Minor, Op. 49 (taken from the Maestro dataset (Hawthorne et al., 2019). For each performance, timing and dynamics are shown using the piano rolls (darker color indicates higher velocity). Pedal control is shown below the piano roll (darker color indicates increasing usage of the pedal). Visualized excerpts correspond to the beginning of the piece.
Table 1
A list of datasets useful for various tasks within MPA.
| name | reference | instruments | genre | data | size | performance parameters |
|---|---|---|---|---|---|---|
| APL | Winters et al. (2016) | piano | classical | audio | 621 recordings | piano practice |
| CBFdataset | Wang et al. (2019) | bamboo flute | chinese | audio | 1GB | playing techniques |
| CrestMusePEDB | Hashida et al. (2008) | piano | classical | xml | 121 performances | timing, dynamics |
| CSD | Cuesta et al. (2018) | vocals | classical | audio, f0 series | 48 recordings | intonation |
| DAMP | – | vocals | popular | audio | 24874 recordings (14 songs) | singing |
| DrumPT | Wu and Lerch (2016) | drums | popular | audio | 30 recordings | playing techniques |
| Duet | Xia and Dannenberg (2015) | piano | classical | MIDI | 105 performances | timing, dynamics |
| EEP | Marchini et al. (2014) | string quartet | classical | audio | 23 recordings | timing, gestures, bowing techniques |
| Erkomaishvili | Rosenzweiget al. (2020) | vocals | Georgian | audio, f0 series, MusicXML | 116 recordings | timing, pitch |
| Groove MIDI | Gillick et al. (2019) | drums | popular | MIDI | 13.6 hours | drum timing |
| GPT | Su et al. (2014) | guitar | popular | audio | 6580 recordings | playing techniques |
| IDMT-SMT-Bass | Abeßer et al. (2010) | bass | popular | audio | 3.6 hours | playing techniques |
| IDMT-SMT-Guitar | Kehling et al. (2014) | guitar | popular | audio | 4700 note events | playing techniques |
| Intonation | Wager et al. (2019) | vocals | popular | audio, f0 series | 4702 performances | singing |
| Jingju-Pitch | Gong et al. (2016) | vocals | Beijing Opera | f0 series | 13MB | intonation |
| JKU-ScoFo | Henkel et al. (2019) | piano | classical | audio, MIDI | 16 performances | timing, dynamics |
| Kara1k | Bayle et al. (2017) | vocals | popular | audio | 1000 songs | singing |
| Maestro | Hawthorne et al. (2019) | piano | classical | audio, MIDI | 200 hours | timing, dynamics |
| MASTmelody | Bozkurt et al. (2017) | vocals | – | f0 series | 1018 recordings | pass/fail ratings |
| MASTrhythm | Falcao et al. (2019) | percussion | – | audio | 3721 recordings | pass/fail ratings |
| Mazurka | Sapp (2007) | piano | classical | beat markers | 2732 recordings | tempo, dynamics |
| PGD | Sarasúa et al. (2017) | piano | classical | audio, video, MIDI | 210 recordings | gestures, intentions |
| QUARTET | Papiotis (2016) | string quartet | classical | audio, video | 96 recordings | timing, gestures, bowing techniques |
| SMD | Müller et al. (2011) | piano | classical | audio, MIDI | 50 performances | timing, dynamics |
| SUPRA | Shi et al. (2019) | piano | classical | piano rolls, MIDI | 478 performances | gestures, timing, dynamics |
| URMP | Li et al. (2019) | multi | classical | audio, video | 44 pieces | timing, dynamics |
| VGD | Sarasúa et al. (2017) | violin | classical | audio, EMG, IMU | 960 recordings | position data, playing techniques |
| Vienna 4x22 | Goebl (1999) | piano | classical | audio, MIDI | 4 pieces, 22 pianists | timing, dynamics |
| VocalSet | Wilkins et al. (2018) | vocals | popular | audio | 6GB | singing techniques |
| WJazzD | Pfleiderer et al. (2017) | wind instruments | jazz | MIDI | 456 solos | timing, pitch |
Figure 3
Schematic showing the comparison between different approaches for music performance assessment.