# Automatic Chord Recognition with Higher-Order Harmonic Language Modelling

arXiv: https://arxiv.org/abs/1808.05341 · HTML: https://mlsanity.com/paper/1808.05341/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Aug 2018.

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

- [Global Structure-Aware Drum Transcription Based on Self-Attention Mechanisms](https://mlsanity.com/paper/2105.05791/) (2021)

## Abstract (arXiv)

Common temporal models for automatic chord recognition model chord changes on a frame-wise basis. Due to this fact, they are unable to capture musical knowledge about chord progressions. In this paper, we propose a temporal model that enables explicit modelling of chord changes and durations. We then apply N-gram models and a neural-network-based acoustic model within this framework, and evaluate the effect of model overconfidence. Our results show that model overconfidence plays only a minor role (but target smoothing still improves the acoustic model), and that stronger chord language models do improve recognition results, however their effects are small compared to other domains.