论文标题
fretnet:用于复音吉他曲面转录的连续值的音高轮廓流
FretNet: Continuous-Valued Pitch Contour Streaming for Polyphonic Guitar Tablature Transcription
论文作者
论文摘要
近年来,自动音乐转录(AMT)的任务,从音频估算音乐笔记的各种属性,受到了越来越多的关注。同时,即使仅隐含地隐含,多线估计的相关任务(MPE)仍然是几乎所有AMT方法的具有挑战性但必要的组成部分。在AMT的背景下,音调信息通常被量化为西方音乐量表的标称音调。即使在更一般的环境中,MPE系统通常会以一定程度的量化产生音高预测。在AMT的某些应用中,例如吉他量表转录(GTT),估计连续值的音高轮廓更有意义。吉他的小组具有表示各种演奏技术的能力,其中一些涉及音高调节。当代AMT的方法不能充分解决音高调制,并且仅提供较少的量化,而牺牲了更复杂的量。在本文中,我们提出了一种GTT公式,该公式估算了连续值的音高轮廓,并根据其弦乐和原点句对它们进行分组。我们证明,对于这项任务,提出的方法显着改善了MPE的分辨率,并同时产生了与基线模型竞争的调头估计结果。
In recent years, the task of Automatic Music Transcription (AMT), whereby various attributes of music notes are estimated from audio, has received increasing attention. At the same time, the related task of Multi-Pitch Estimation (MPE) remains a challenging but necessary component of almost all AMT approaches, even if only implicitly. In the context of AMT, pitch information is typically quantized to the nominal pitches of the Western music scale. Even in more general contexts, MPE systems typically produce pitch predictions with some degree of quantization. In certain applications of AMT, such as Guitar Tablature Transcription (GTT), it is more meaningful to estimate continuous-valued pitch contours. Guitar tablature has the capacity to represent various playing techniques, some of which involve pitch modulation. Contemporary approaches to AMT do not adequately address pitch modulation, and offer only less quantization at the expense of more model complexity. In this paper, we present a GTT formulation that estimates continuous-valued pitch contours, grouping them according to their string and fret of origin. We demonstrate that for this task, the proposed method significantly improves the resolution of MPE and simultaneously yields tablature estimation results competitive with baseline models.