Polyphonic Music Transcription with Semantic Segmentation
Yu‐Te Wu, Berlin Chen, Li Su · 2019
The multi-instrument transcription task refers to joint recognition of instrument and pitch of every event in polyphonic music signals generated by one or more classes of music instruments. In this paper, we leverage multi-object semantic segmentation techniques to solve this problem. We design a time-frequency representation, which has multiple channels to jointly represent the harmonic structure and pitch saliency of a pitch activation. The transcription task therefore becomes a pixel-wise multi-task classification problem including pitch activity detection and instrument recognition. Experiments on both single- and multi-instrument data verify the competitiveness of the proposed method.