From music audio to chord tablature: Teaching deep convolutional networks toplay guitar

Eric J. Humphrey, Juan P. Bello
2014 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
Automatic chord recognition is conventionally tackled as a general music audition task, where the desired output is a time-aligned sequence of discrete chord symbols, e.g. CMaj7, Esus2, etc. In practice, however, this presents two related challenges: one, the act of decoding a given chord sequence requires that the musician knows both the notes in the chord and how to play them on some instrument; and two, chord labeling systems do not degrade gracefully for users without significant musical
more » ... nificant musical training. Alternatively, we address both challenges by modeling the physical constraints of a guitar to produce human-readable representations of music audio, i.e guitar tablature via a deep convolutional network. Through training and evaluation as a standard chord recognition system, the model is able to yield representations that require minimal prior knowledge to interpret, while maintaining respectable performance compared to the state of the art.
doi:10.1109/icassp.2014.6854952 dblp:conf/icassp/HumphreyB14 fatcat:ndmnnajr4zcr5jijlwbjf2uoue