Update README.md

README.md

@@ -82,19 +82,16 @@ tags:
 
 ### Dataset Summary
 
-VIVOS is a free Vietnamese speech corpus consisting of 15 hours of recording speech prepared for Vietnamese Automatic Speech Recognition task.
-
-The corpus was prepared by AILAB, a computer science lab of VNUHCM - University of Science, with Prof. Vu Hai Quan is the head of.
-
-We publish this corpus in hope to attract more scientists to solve Vietnamese speech recognition problems.
+SUBAK.KO is a Bangladeshi standard Bangla annotated speech corpus for automatic speech recognition research. The corpus contains 241 hours
+of high quality speech data, including 229 hours of read speech data collected in an studio environment and 12 hours of broadcast speech data.
 
 ### Supported Tasks and Leaderboards
 
-[Needs More Information]
+This dataset is designed for the automatic speech recognition task. The associated paper provides the baseline results on SUBAK.KO corpus. 
 
 ### Languages
 
-Vietnamese
+Bangladeshi standard Bangla
 
 ## Dataset Structure
 
@@ -191,20 +188,13 @@ Public Domain, Creative Commons Attribution NonCommercial ShareAlike v4.0 ([CC B
 ### Citation Information
 
 ```
-@inproceedings{luong-vu-2016-non,
-    title = "A non-expert {K}aldi recipe for {V}ietnamese Speech Recognition System",
-    author = "Luong, Hieu-Thi  and
-      Vu, Hai-Quan",
-    booktitle = "Proceedings of the Third International Workshop on Worldwide Language Service Infrastructure and Second Workshop on Open Infrastructures and Analysis Frameworks for Human Language Technologies ({WLSI}/{OIAF}4{HLT}2016)",
-    month = dec,
-    year = "2016",
-    address = "Osaka, Japan",
-    publisher = "The COLING 2016 Organizing Committee",
-    url = "https://aclanthology.org/W16-5207",
-    pages = "51--55",
+@article{kibria2022bangladeshi,
+  title={Bangladeshi Bangla speech corpus for automatic speech recognition research},
+  author={Kibria, Shafkat and Samin, Ahnaf Mozib and Kobir, M Humayon and Rahman, M Shahidur and Selim, M Reza and Iqbal, M Zafar},
+  journal={Speech Communication},
+  volume={136},
+  pages={84--97},
+  year={2022},
+  publisher={Elsevier}
 }
-```
-
-### Contributions
-
-Thanks to [@binh234](https://github.com/binh234) for adding this dataset.
+```