| # BanglaBeats Dataset | |
| ## Overview | |
| BanglaBeats is a comprehensive dataset of Bengali songs created for music genre classification tasks. The dataset consists of 1617 audio samples, each lasting for 30 seconds, and spans across 8 distinct music genres. Each 30-second audio clip is divided into 10 shorter clips, each lasting for 3 seconds, as part of the augmentation process. | |
| ## Citation | |
| If you use BanglaBeats in your research, please cite the following paper: | |
| **Title:** BanglaBeats: A Comprehensive Dataset of Bengali Songs for Music Genre Classification Tasks | |
| **Authors:** Md. Mehedi Hasan Jibon, Dewan Mahinur Alam, Mohammad Shahidur Rahman | |
| **Conference:** 2023 26th International Conference on Computer and Information Technology (ICCIT) | |
| **DOI:** [10.1109/iccit60459.2023.10441288](http://dx.doi.org/10.1109/iccit60459.2023.10441288) | |
| ## Dataset Links | |
| - Kaggle: [BanglaBeats on Kaggle](https://www.kaggle.com/datasets/thisisjibon/banglabeats3sec/data) | |
| - Hugging Face: [BanglaBeats on Hugging Face](https://huggingface.co/datasets/thisisjibon/banglabeats) | |
| ## BibTeX: | |
| ```bibtex | |
| @inproceedings{jibon2023banglabeats, | |
| title={BanglaBeats: A Comprehensive Dataset of Bengali Songs for Music Genre Classification Tasks}, | |
| author={Jibon, Md Mehedi Hasan and Alam, Dewan Mahinur and Rahman, Mohammad Shahidur}, | |
| booktitle={2023 26th International Conference on Computer and Information Technology (ICCIT)}, | |
| pages={1--6}, | |
| year={2023}, | |
| organization={IEEE} | |
| } | |