Update README.md

README.md

@@ -28,16 +28,21 @@ We release four gender-specific models trained on 1K hours of speech.
 Pretrained wav2vec2 models are distributed under the Apache-2.0 license. Hence, they can be reused extensively without strict limitations. However, benchmarks and data may be linked to corpora that are not completely open-sourced.
 
 ## Referencing our gender-specific models
-
-<soon to be added>
-
+```
+@article{boito2022study,
+  title={A Study of Gender Impact in Self-supervised Models for Speech-to-Text Systems},
+  author={Marcely Zanon Boito and Laurent Besacier and Natalia Tomashenko and Yannick Est{\`e}ve}, 
+  journal={arXiv preprint arXiv:2204.01397},
+  year={2022}
+}
+```
 ## Referencing LeBenchmark
 
 ```
-@article{Evain2021LeBenchmarkAR,
-  title={LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech},
-  author={Sol{\`e}ne Evain and Ha Nguyen and Hang Le and Marcely Zanon Boito and Salima Mdhaffar and Sina Alisamir and Ziyi Tong and N. Tomashenko and Marco Dinarelli and Titouan Parcollet and A. Allauzen and Y. Est{\`e}ve and B. Lecouteux and F. Portet and S. Rossato and F. Ringeval and D. Schwab and L. Besacier},
-  journal={ArXiv},
-  year={2021},
-  volume={abs/2104.11462}
-}
+@inproceedings{evain2021task,
+  title={Task agnostic and task specific self-supervised learning from speech with \textit{LeBenchmark}},
+  author={Evain, Sol{\`e}ne and Nguyen, Ha and Le, Hang and Boito, Marcely Zanon and Mdhaffar, Salima and Alisamir, Sina and Tong, Ziyi and Tomashenko, Natalia and Dinarelli, Marco and Parcollet, Titouan and others},
+  booktitle={Thirty-fifth  Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)},
+  year={2021}
+}
+```