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language:
- en
license: cc-by-nc-4.0
tags:
- music
- audio
- multimodal
- regression
- aesthetics
- dataset
---
# MADB: Music Aesthetics Dataset and Benchmark
## Dataset Description
MADB is a large-scale dataset for music aesthetic evaluation, designed to support research on multi-dimensional and subjective music perception.
The dataset contains approximately **10,000 music tracks**, each annotated by **multiple trained annotators** across **10 perceptual dimensions** and one overall score. In addition, each track includes **textual comments** and **semantic tags** (genre and mood), enabling multimodal learning.
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## Data Composition
### Audio
- All audio files are stored under `data/audio/` (mp3 format)
- 1730 tracks are generated by Suno and Levo
- 4400 tracks are from the Muchin dataset: https://github.com/CarlWangChina/MuChin
- Remaining tracks are collected from diverse online sources
---
### Annotations
Annotations are stored under `data/annotation/`:
- `avg_score.csv`: average score for each dimension per track
- `MADB_data.csv`: full annotation data, including:
- per-annotator scores
- textual comments
- genre and mood tags
- `split_val_seed5.csv`: the validate set with random seed 5
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### Sample
Samples are stored under `sample/`:
- sample_audio: 200 audios selected from validate set:
- 100 audios randomly selected from Muchin
- 50 audios from levo
- 50 audios from suno
- sample_embedding: embedding extracted from sample audios:
- clap: extracted with original clap
- muq: extracted with original muq
- clap_com: extracted with clap after adaption with comments
- clap_com_tag: extracted with clap after adaption with comments and tags
- `sample_ids.csv`: contains all sample audios' id
---
## Annotation Framework
Each track is rated across the following dimensions:
- Melody perception
- Melody emotion
- Arrangement perception
- Arrangement emotion
- Rhythm perception
- Structure perception
- Performance and singing mood
- Enunciation and singing skill
- Performance skill
- Sound effect perception
- Overall score
Some dimensions may be **not applicable**, in which case a value of `0` is assigned.
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## Annotation Process
- Annotators have at least **3 years of formal music training**
- All annotators hold at least a **bachelor's degree**
- Quality control is conducted by experts with **10+ years of professional experience**
- Each track is rated by multiple annotators
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## Intended Use
This dataset is designed for:
- Music aesthetic evaluation
- Multimodal learning (audio + text + tags)
- Music understanding and analysis
- Evaluation of generative music systems
---
## Licensing and Usage
- Audio data may be subject to original copyright restrictions
- Users should ensure compliance with the original data sources
- This dataset is intended for **research purposes only**
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