Evaluating Automatic Polyphonic Music Transcription

Andrew McLeod, Mark Steedman
2018 Zenodo  
Automatic Music Transcription (AMT) is an important task in music information retrieval. Prior work has focused on multiple fundamental frequency estimation (multi-pitch detection), the conversion of an audio signal into a timefrequency representation such as a MIDI file. It is less common to annotate this output with musical features such as voicing information, metrical structure, and harmonic information, though these are important aspects of a complete transcription. Evaluation of these
more » ... ures is most often performed separately and independent of multi-pitch detection; however, these features are non-independent. We therefore introduce M V 2H, a quantitative, automatic, joint evaluation metric based on musicological principles, and show its effectiveness through the use of specific examples. The metric is modularised in such a way that it can still be used with partially performed annotation— for example, when the transcription process has been applied to some transduced format such as MIDI (which may itself be the result of multi-pitch detection). The code for the evaluation metric described here is available at https://www.github.com/apmcleod/MV2H.
doi:10.5281/zenodo.1492338 fatcat:hrfrd5wpibbznneoxwbcfahz4i