Update README.md

README.md

@@ -46,4 +46,20 @@ The dataset contains three subsets:
 - 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 3 Jan, 2025]* Our paper has been accepted to ICASSP 2025! The preprint is available at: https://arxiv.org/abs/2501.00328.
+*[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}}
+
+```