论文标题
巴赫还是模拟？ J.S.的合唱的分级功能巴赫
Bach or Mock? A Grading Function for Chorales in the Style of J.S. Bach
论文作者
论文摘要
与传统的基于规则的系统相比，从现有音乐语料库中学习概率模型的深层生成系统不会明确编码音乐风格的知识。因此，在没有专家评估的情况下，很难确定深层模型是否会产生风格上正确的输出，但这是昂贵且耗时的。因此，需要自动，可解释和音乐动机的评估措施。在本文中，我们介绍了一种分级函数，该函数以J.S.的风格评估了四部分合唱团。 Bach沿着重要的音乐功能。我们使用分级函数来评估变压器模型的输出，并表明该函数既可以解释，又超过了人类专家，可以将Bach唱片与模型生成的函数区分开。
Deep generative systems that learn probabilistic models from a corpus of existing music do not explicitly encode knowledge of a musical style, compared to traditional rule-based systems. Thus, it can be difficult to determine whether deep models generate stylistically correct output without expert evaluation, but this is expensive and time-consuming. Therefore, there is a need for automatic, interpretable, and musically-motivated evaluation measures of generated music. In this paper, we introduce a grading function that evaluates four-part chorales in the style of J.S. Bach along important musical features. We use the grading function to evaluate the output of a Transformer model, and show that the function is both interpretable and outperforms human experts at discriminating Bach chorales from model-generated ones.
