# Bach or Mock? A Grading Function for Chorales in the Style of J.S. Bach

arXiv: https://arxiv.org/abs/2006.13329 · HTML: https://mlsanity.com/paper/2006.13329/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jun 2020.

## Built on by (most cited first, 1 of 1)

- [Adaptive Accompaniment with ReaLchords](https://mlsanity.com/paper/2506.14723/) (2025)

## Abstract (arXiv)

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.