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In this paper, we propose a new dataset named EGDB, that con-tainstranscriptions of the electric guitar performance of 240 tab-latures renderedwith different tones. Moreover, we benchmark theperformance of two well-knowntranscription models proposed orig-inally for the piano on this dataset, alongwith a multi-loss Trans-former model that we newly propose. Our evaluation onthis datasetand a separate set of real-world recordings demonstrate theinfluenceof timbre on the accuracy of guitar sheet transcription, thepotentialof using multiple losses for Transformers, as well as the roomforfurther improvement for this task.

towards automatic transcription of polyphonic electric guitar music:a new dataset and a multi-loss transformer model