Update README.md

README.md

@@ -49,7 +49,7 @@ size_categories:
 ## Dataset Description
 
 - **Developed By** Dept. of CSE, SUST, Bangladesh
-- **Paper:** [BanSpeech: A Multi-domain Bangla Speech Recognition Benchmark Toward Robust Performance in Challenging Conditions](https://www.sciencedirect.com/science/article/abs/pii/S0167639321001370)
+- **Paper:** [BanSpeech: A Multi-domain Bangla Speech Recognition Benchmark Toward Robust Performance in Challenging Conditions](https://ieeexplore.ieee.org/document/10453554)
 - **Point of Contact:** [Ahnaf Mozib Samin, Dept. of CSE, SUST](mailto:[email protected])
 
 ### Dataset Summary
@@ -58,7 +58,7 @@ BanSpeech is a publicly available human-annotated Bangladeshi standard Bangla mu
 This benchmark contains approximately 6.52 hours of human-annotated broadcast speech, totaling 8085 utterances, across 13 distinct domains and 
 is primarily designed for ASR performance evaluation in challenging conditions e.g. spontaneous, domain-shifting, multi-talker, code-switching. 
 In addition, BanSpeech covers dialectal domains from 7 regions of Bangladesh, however, this part is weakly labeled and can be used for dialect recognition task. 
-The [corresponding paper](https://www.sciencedirect.com/science/article/abs/pii/S0167639321001370) reports 
+The [corresponding paper](https://ieeexplore.ieee.org/document/10453554) reports 
 detailed information about the development of BanSpeech, along with an analysis of the performance of state-of-the-art 
 fully supervised, self-supervised, and weakly supervised models on BanSpeech.
 
@@ -132,15 +132,16 @@ A typical data point comprises the path to the audio file and its transcription.
 Please cite the following paper if you use the corpus.
 
 ```
-@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}
-}
+@ARTICLE{10453554,
+  author={Samin, Ahnaf Mozib and Kobir, M. Humayon and Rafee, Md. Mushtaq Shahriyar and Ahmed, M. Firoz and Hasan, Mehedi and Ghosh, Partha and Kibria, Shafkat and Rahman, M. Shahidur},
+  journal={IEEE Access}, 
+  title={BanSpeech: A Multi-Domain Bangla Speech Recognition Benchmark Toward Robust Performance in Challenging Conditions}, 
+  year={2024},
+  volume={12},
+  number={},
+  pages={34527-34538},
+  keywords={Speech recognition;Data models;Benchmark testing;Speech processing;Robustness;Solid modeling;Task analysis;Automatic speech recognition;Transfer learning;Neural networks;Convolutional neural networks;Supervised learning;Automatic speech recognition;Bangla;domain shifting;read speech;spontaneous speech;transfer learning},
+  doi={10.1109/ACCESS.2024.3371478}}
 ```
 
 ### Contributions