# Towards Music Captioning: Generating Music Playlist Descriptions

arXiv: https://arxiv.org/abs/1608.04868 · HTML: https://mlsanity.com/paper/1608.04868/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Aug 2016.

## Built on by (most cited first, 7 of 7)

- [A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT](https://mlsanity.com/paper/2303.04226/) (2023)
- [MusiLingo: Bridging Music and Text with Pre-trained Language Models for Music Captioning and Query Response](https://mlsanity.com/paper/2309.08730/) (2023)
- [Contrastive Audio-Language Learning for Music](https://mlsanity.com/paper/2208.12208/) (2022)
- [MusCaps: Generating Captions for Music Audio](https://mlsanity.com/paper/2104.11984/) (2021)
- [Music-to-Text Synaesthesia: Generating Descriptive Text from Music Recordings](https://mlsanity.com/paper/2210.00434/) (2022)
- [Music Playlist Title Generation Using Artist Information](https://mlsanity.com/paper/2301.08145/) (2023)
- [Music Playlist Captioning at Scale with Large Language Models](https://mlsanity.com/paper/2606.22460/) (2026)

## Abstract (arXiv)

Descriptions are often provided along with recommendations to help users' discovery. Recommending automatically generated music playlists (e.g. personalised playlists) introduces the problem of generating descriptions. In this paper, we propose a method for generating music playlist descriptions, which is called as music captioning. In the proposed method, audio content analysis and natural language processing are adopted to utilise the information of each track.