Update README.md

README.md

@@ -9,17 +9,16 @@ tags:
 - speech-to-speech-translation
 
 datasets:
-- mtedx
-- covost2
-- europarl_st
-- voxpopuli
+- Must-C
+- TAT
+- Hokkien dramas
 
 ---
 ## xm_transformer_s2ut_hk-en
 
-Speech-to-speech translation model from fairseq S2UT ([paper](https://arxiv.org/abs/2204.02967)/[code](https://github.com/facebookresearch/fairseq/blob/main/examples/speech_to_speech/docs/enhanced_direct_s2st_discrete_units.md)):
+Speech-to-speech translation model from fairseq:
 - Hokkien-English
-- Trained on mTEDx, CoVoST 2, Europarl-ST and VoxPopuli
+- Trained on MuST-C, TAT and Hokkien dramas
 - Speech synthesis with [facebook/unit_hifigan_mhubert_vp_en_es_fr_it3_400k_layer11_km1000_lj_dur](https://huggingface.co/facebook/unit_hifigan_mhubert_vp_en_es_fr_it3_400k_layer11_km1000_lj_dur)
 
 ## Usage
@@ -89,17 +88,3 @@ wav, sr = tts_model.get_prediction(tts_sample)
 
 ipd.Audio(wav, rate=sr)
 ```
-
-## Citation
-```bibtex
-@misc{https://doi.org/10.48550/arxiv.2204.02967,
-  doi = {10.48550/ARXIV.2204.02967},  
-  url = {https://arxiv.org/abs/2204.02967},  
-  author = {Popuri, Sravya and Chen, Peng-Jen and Wang, Changhan and Pino, Juan and Adi, Yossi and Gu, Jiatao and Hsu, Wei-Ning and Lee, Ann},  
-  keywords = {Computation and Language (cs.CL), Sound (cs.SD), Audio and Speech Processing (eess.AS), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering},  
-  title = {Enhanced Direct Speech-to-Speech Translation Using Self-supervised Pre-training and Data Augmentation},  
-  publisher = {arXiv},  
-  year = {2022},  
-  copyright = {arXiv.org perpetual, non-exclusive license}
-}
-```