README.md

---
dataset_info:
  features:
  - name: audio
    struct:
    - name: array
      sequence: float64
    - name: sampling_rate
      dtype: int64
  - name: speaker
    dtype: string
  splits:
  - name: train_small
    num_bytes: 59215473264
    num_examples: 83000
  - name: test
    num_bytes: 18734546245
    num_examples: 26523
  - name: train
    num_bytes: 101784602791
    num_examples: 161457
  download_size: 44153221262
  dataset_size: 179734622300
configs:
- config_name: default
  data_files:
  - split: train_small
    path: data/train_small-*
  - split: test
    path: data/test-*
  - split: train
    path: data/train-*
license: cc
language:
- vi
tags:
- speaker-recognition
- speaker-verification
- vietnamese-speech-processing
pretty_name: voxvietnam
size_categories:
- 100K<n<1M
---
The dataset contains three subsets:
- train: Official training set (`VoxVietnam-T`) used in the paper (1,256 speakers, 161,457 samples).  
- train_small: `VoxVietnam-T-small`, sampled from VoxVietnam-T to have the same size as Vietnam-Celeb (879 speakers, 83,000 samples).  
- The `VoxVietnam-T-noisy` in the paper is not uploaded since it is not clean for supervised training, just for ablation studies in the paper only.  

*[Update 29 Mar, 2025]* The VoxVietnam-E and VoxVietnam-H are labelled by volunteers without visual information. Our team released another independent test set, called `VoxVietnam-O`, verified by us by listening and watching the video segments for the highest accuracy. The speakers in `VoxVietnam-O` are sampled from the `test` partition. You can download the data and test list for `VoxVietnam-O` [here](https://drive.google.com/drive/folders/1k8CZcxXXygu1YzaIDPceV38ngdlKMEO6?usp=sharing). __We encourage researchers to use VoxVietnam-O for evaluation.__   
Here are the results on VoxVietnam-O for reference. We use [Ruijie Tao's](https://github.com/TaoRuijie/ECAPA-TDNN/) implementation of ECAPA-TDNN:  
| Train                          | EER (%) | minDCF (%) |
|--------------------------------|---------|------------|
| VoxVietnam-T                   | 3.03    | 0.4781     |
| Vietnam-Celeb-T                | 3.25    | 0.5376     |
| VoxVietnam-T-small             | 3.96    | 0.5273     |
| VoxVietnam-T-noisy             | 6.91    | 0.6813     |
| Vietnam-Celeb-T + VoxVietnam-T | 3.34    | 0.5286     |


*[Update 03 Jan, 2025]* Our paper has been accepted to ICASSP 2025! The preprint is available at: https://arxiv.org/abs/2501.00328.  

Please cite our work as:
```
@INPROCEEDINGS{10890124,
  author={Vu, Hoang Long and Dat, Phuong Tuan and Nhi, Pham Thao and Hao, Nguyen Song and Thu Trang, Nguyen Thi},
  booktitle={ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 
  title={VoxVietnam: a Large-Scale Multi-Genre Dataset for Vietnamese Speaker Recognition}, 
  year={2025},
  volume={},
  number={},
  pages={1-5},
  doi={10.1109/ICASSP49660.2025.10890124}}

```