论文标题
迈向复音电吉他音乐的自动转录：新数据集和多损失变压器模型
towards automatic transcription of polyphonic electric guitar music:a new dataset and a multi-loss transformer model
论文作者
论文摘要
在本文中，我们提出了一个名为EGDB的新数据集，该数据集构成了用不同音调呈现的240个Tab latures的电吉他性能的转录。此外，我们基于在该数据集上为钢琴提出的两个知名转录模型的性能以及我们新提出的多层状反式模型。我们对此数据集的评估和单独的一组实际录音表明，音色的影响对吉他纸转录的准确性，对变压器进行多个损失的电位以及此任务的改进的房间。
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.
