# Classifying Songs with EEG

arXiv: https://arxiv.org/abs/2010.04087 · HTML: https://mlsanity.com/paper/2010.04087/

## Key facts

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

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

- [Predicting Artificial Neural Network Representations to Learn Recognition Model for Music Identification from Brain Recordings](https://mlsanity.com/paper/2412.15560/) (2024)

## Abstract (arXiv)

This research study aims to use machine learning methods to characterize the EEG response to music. Specifically, we investigate how resonance in the EEG response correlates with individual aesthetic enjoyment. Inspired by the notion of musical processing as resonance, we hypothesize that the intensity of an aesthetic experience is based on the degree to which a participants EEG entrains to the perceptual input. To test this and other hypotheses, we have built an EEG dataset from 20 subjects listening to 12 two minute-long songs in random order. After preprocessing and feature construction, we used this dataset to train and test multiple machine learning models.