The quality of Optical Music Recognition (OMR) systems is a rather difficult magnitude to measure. There is no lingua franca shared among OMR datasets that allows to compare systems' performance on equal grounds, since most of them are specialised on certain approaches. As a result, most state-of-the-art works currently report metrics that cannot be compared directly. In this paper we identify the need of a common music representation language and propose the Music Tree Notation (MTN) format, thanks to which the definition of standard metrics is possible. This format represents music as a set of primitives that group together into higher-abstraction nodes, a compromise between the expression of fully graph-based and sequential notation formats. We have also developed a specific set of OMR metrics and a typeset score dataset as a proof of concept of this idea.

翻译：光学乐谱识别（OMR）系统的质量是一个相当难以衡量的指标。由于目前缺乏OMR数据集之间通用的标准语言，使得无法在同等条件下比较不同系统的性能，因为大多数数据集都针对特定方法进行了专门化。因此，现有的大多数前沿研究成果所报告的指标无法直接进行比较。本文指出了通用音乐表示语言的必要性，并提出了音乐树符号（MTN）格式，通过该格式可以定义标准化指标。该格式将音乐表示为一组基本元素，这些元素组合成更高抽象层次的节点，是完整的基于图的符号格式与序列化符号格式之间的折中方案。我们还开发了一套特定的OMR指标和排版乐谱数据集，作为这一概念的验证性实现。