论文标题
在完整的分数图中学习阅读和关注音乐
Learning to Read and Follow Music in Complete Score Sheet Images
论文作者
论文摘要
本文介绍了以未经处理的图像给出的乐谱中得分的任务。尽管现有工作要么依赖OMR软件来获得计算机可读的分数表示形式，要么至关重要的是依赖准备的表映像摘录，但我们提出了第一个直接在完整页面，完全未经处理的纸张图像下执行得分的系统。基于传入的音频和分数的给定图像，我们的系统直接预测了与音频匹配的页面中最有可能的位置，从而优于基于图像的当前图像分数关注者，从而对准精度。我们还将我们的方法与基于OMR的方法进行比较，并从经验上表明它可以成为这种系统的可行替代方法。
This paper addresses the task of score following in sheet music given as unprocessed images. While existing work either relies on OMR software to obtain a computer-readable score representation, or crucially relies on prepared sheet image excerpts, we propose the first system that directly performs score following in full-page, completely unprocessed sheet images. Based on incoming audio and a given image of the score, our system directly predicts the most likely position within the page that matches the audio, outperforming current state-of-the-art image-based score followers in terms of alignment precision. We also compare our method to an OMR-based approach and empirically show that it can be a viable alternative to such a system.
