Scorpiano -- A System for Automatic Music Transcription for Monophonic Piano Music
This work addresses the problem of quickly generating music scores for piano players, from beginners to experts, but is incremental as it focuses on simple monophonic melodies.
The authors tackled automatic music transcription for monophonic piano music by developing Scorpiano, a system using digital signal processing methods like onset detection and pitch detection, which achieved results comparable to commercial neural network systems for simple melodies.
Music transcription is the process of transcribing music audio into music notation. It is a field in which the machines still cannot beat human performance. The main motivation for automatic music transcription is to make it possible for anyone playing a musical instrument, to be able to generate the music notes for a piece of music quickly and accurately. It does not matter if the person is a beginner and simply struggles to find the music score by searching, or an expert who heard a live jazz improvisation and would like to reproduce it without losing time doing manual transcription. We propose Scorpiano -- a system that can automatically generate a music score for simple monophonic piano melody tracks using digital signal processing. The system integrates multiple digital audio processing methods: notes onset detection, tempo estimation, beat detection, pitch detection and finally generation of the music score. The system has proven to give good results for simple piano melodies, comparable to commercially available neural network based systems.