  In this paper, we propose a new dataset named EGDB, that con-tains
transcriptions of the electric guitar performance of 240 tab-latures rendered
with different tones. Moreover, we benchmark theperformance of two well-known
transcription models proposed orig-inally for the piano on this dataset, along
with a multi-loss Trans-former model that we newly propose. Our evaluation on
this datasetand a separate set of real-world recordings demonstrate the
influenceof timbre on the accuracy of guitar sheet transcription, the
potentialof using multiple losses for Transformers, as well as the room
forfurther improvement for this task.
