Datasets:
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---
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.__
*[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}}
``` |