Audio-based guitar tablature transcription using multipitch analysis and playability constraints

This paper proposes a method of guitar tablature transcription from audio signals. Multipitch estimation and fingering configuration estimation are essential for transcribing tablatures. Conventional multipitch estimation methods, including latent harmonic allocation (LHA), often estimate combinations of pitches that people cannot play due to inherent physical constraints. Unplayable combinations of pitches are eliminated by filtering the results of LHA with three constraints. We first enumerate playable fingering configurations, and use them to suppress any undesirable combination of pitches. The optimal fingering configuration in each time frame is optimized to satisfy the need for temporal continuity by using dynamic programming. We use synthesized guitar sounds from MIDI data (ground truth) for evaluation. Experiments with them demonstrate the improvement of multipitch estimation by 5.9 points on average in F-measure and the transcribed tablatures are playable.