| --- |
| language: |
| - en |
| license: cc-by-nc-4.0 |
| tags: |
| - music |
| - audio |
| - multimodal |
| - regression |
| - aesthetics |
| - dataset |
| --- |
| |
| # MADB: Music Aesthetics Dataset and Benchmark |
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| ## Dataset Description |
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| MADB is a large-scale dataset for music aesthetic evaluation, designed to support research on multi-dimensional and subjective music perception. |
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| 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 |
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| ### Audio |
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| - 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 |
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| --- |
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| ### Annotations |
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| Annotations are stored under `data/annotation/`: |
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| - `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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| --- |
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| ### Sample |
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| Samples are stored under `sample/`: |
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| - 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 |
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| --- |
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| ## Annotation Framework |
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| Each track is rated across the following dimensions: |
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| - 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 |
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| Some dimensions may be **not applicable**, in which case a value of `0` is assigned. |
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| --- |
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| ## Annotation Process |
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| - 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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| --- |
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| ## Intended Use |
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| This dataset is designed for: |
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| - Music aesthetic evaluation |
| - Multimodal learning (audio + text + tags) |
| - Music understanding and analysis |
| - Evaluation of generative music systems |
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| --- |
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| ## Licensing and Usage |
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| - 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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