# Melon Playlist Dataset: a public dataset for audio-based playlist generation and music tagging

arXiv: https://arxiv.org/abs/2102.00201 · HTML: https://mlsanity.com/paper/2102.00201/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 19 references that are in the map.
- First posted on arXiv 30 Jan 2021.

## Builds on (most cited first, 4 of 4)

- [FMA: A Dataset For Music Analysis](https://mlsanity.com/paper/1612.01840/) (2016)
- [Convolutional Recurrent Neural Networks for Music Classification](https://mlsanity.com/paper/1609.04243/) (2016)
- [Current Challenges and Visions in Music Recommender Systems Research](https://mlsanity.com/paper/1710.03208/) (2017)
- [An Analysis of Approaches Taken in the ACM RecSys Challenge 2018 for Automatic Music Playlist Continuation](https://mlsanity.com/paper/1810.01520/) (2018)

## Built on by (most cited first, 5 of 5)

- [A Scalable Framework for Automatic Playlist Continuation on Music Streaming Services](https://mlsanity.com/paper/2304.09061/) (2023)
- [Music Playlist Title Generation: A Machine-Translation Approach](https://mlsanity.com/paper/2110.07354/) (2021)
- [Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation](https://mlsanity.com/paper/2507.15826/) (2025)
- [Music Playlist Title Generation Using Artist Information](https://mlsanity.com/paper/2301.08145/) (2023)
- [S2Cap: A Benchmark and a Baseline for Singing Style Captioning](https://mlsanity.com/paper/2409.09866/) (2024)

## Abstract (arXiv)

One of the main limitations in the field of audio signal processing is the lack of large public datasets with audio representations and high-quality annotations due to restrictions of copyrighted commercial music. We present Melon Playlist Dataset, a public dataset of mel-spectrograms for 649,091tracks and 148,826 associated playlists annotated by 30,652 different tags. All the data is gathered from Melon, a popular Korean streaming service. The dataset is suitable for music information retrieval tasks, in particular, auto-tagging and automatic playlist continuation. Even though the latter can be addressed by collaborative filtering approaches, audio provides opportunities for research on track suggestions and building systems resistant to the cold-start problem, for which we provide a baseline. Moreover, the playlists and the annotations included in the Melon Playlist Dataset make it suitable for metric learning and representation learning.