# 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}
}