Datasets:
Size:
10K<n<100K
License:
license: mit | |
task_categories: | |
- audio-classification | |
language: | |
- zh | |
- en | |
tags: | |
- music | |
- art | |
pretty_name: Music Genre Dataset | |
size_categories: | |
- 10K<n<100K | |
viewer: false | |
# Dataset Card for Music Genre | |
## Dataset Description | |
- **Homepage:** <https://ccmusic-database.github.io> | |
- **Repository:** <https://huggingface.co/datasets/ccmusic-database/music_genre> | |
- **Paper:** <https://doi.org/10.5281/zenodo.5676893> | |
- **Leaderboard:** <https://ccmusic-database.github.io/team.html> | |
- **Point of Contact:** N/A | |
### Dataset Summary | |
This database contains about 1700 musical pieces (.mp3 format) with lengths of 270-300s that are divided into 17 genres in total. | |
### Supported Tasks and Leaderboards | |
Audio classification | |
### Languages | |
Multilingual | |
## Usage | |
When doing classification task, only one colum of fst_level_label, sec_level_label and thr_level_label can be used, not for mixing. | |
``` | |
from datasets import load_dataset | |
dataset = load_dataset("ccmusic-database/music_genre", split="test") | |
for item in dataset: | |
print(item) | |
``` | |
## Dataset Structure | |
| mel | cqt | chroma | fst_level_label | sec_level_label | thr_level_label | | |
| :---: | :---: | :----: | :-------------: | :-------------: | :-------------: | | |
| jpg | jpg | jpg | 2-class | 9-class | 12-class | | |
### Data Instances | |
.zip(.jpg) | |
### Data Fields | |
``` | |
1_Classic | |
3_Symphony | |
4_Opera | |
5_Solo | |
6_Chamber | |
2_Non_classic | |
7_Pop | |
12_Pop_vocal_ballad | |
13_Adult_contemporary | |
14_Teen_pop | |
8_Dance_and_house | |
15_Contemporary_dance_pop | |
16_Dance_pop | |
9_Indie | |
17_Classic_indie_pop | |
18_Chamber_cabaret_and_art_pop | |
10_Soul_or_r_and_b | |
11_Rock | |
19_Adult_alternative_rock | |
20_Uplifting_anthemic_rock | |
21_Soft_rock | |
22_Acoustic_pop | |
0_None | |
``` | |
### Data Splits | |
Train(80%), valid(10%), test(10%) | |
## Dataset Creation | |
### Curation Rationale | |
Promoting the development of AI in the music industry | |
### Source Data | |
#### Initial Data Collection and Normalization | |
Zhaorui Liu, Monan Zhou | |
#### Who are the source language producers? | |
Composers of the songs in dataset | |
### Annotations | |
#### Annotation process | |
Students collected about 1700 musical pieces (.mp3 format) with lengths of 270-300s divided into 17 genres in total. | |
#### Who are the annotators? | |
Students from CCMUSIC | |
### Personal and Sensitive Information | |
Due to copyright issues with the original music, only mel spectrograms are provided in the dataset. | |
## Considerations for Using the Data | |
### Social Impact of Dataset | |
Promoting the development of AI in the music industry | |
### Discussion of Biases | |
Most are English songs | |
### Other Known Limitations | |
Samples are not balanced enough | |
## Additional Information | |
### Dataset Curators | |
Zijin Li | |
### Evaluation | |
Coming soon... | |
### Licensing Information | |
``` | |
MIT License | |
Copyright (c) CCMUSIC | |
Permission is hereby granted, free of charge, to any person obtaining a copy | |
of this software and associated documentation files (the "Software"), to deal | |
in the Software without restriction, including without limitation the rights | |
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
copies of the Software, and to permit persons to whom the Software is | |
furnished to do so, subject to the following conditions: | |
The above copyright notice and this permission notice shall be included in all | |
copies or substantial portions of the Software. | |
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | |
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | |
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | |
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | |
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | |
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | |
SOFTWARE. | |
``` | |
### Citation Information | |
``` | |
@dataset{zhaorui_liu_2021_5676893, | |
author = {Zhaorui Liu, Monan Zhou, Shenyang Xu, Yuan Wang, Zhaowen Wang, Wei Li and Zijin Li}, | |
title = {CCMUSIC DATABASE: A Music Data Sharing Platform for Computational Musicology Research}, | |
month = {nov}, | |
year = {2021}, | |
publisher = {Zenodo}, | |
version = {1.1}, | |
doi = {10.5281/zenodo.5676893}, | |
url = {https://doi.org/10.5281/zenodo.5676893} | |
} | |
``` | |
### Contributions | |
Provide a dataset for music genre classification |