Update README.md

README.md

@@ -160,25 +160,16 @@ In this work, we introduce *MultiMed*, a collection of small-to-large end-to-end
 To our best knowledge, *MultiMed* stands as **the largest and the first multilingual medical ASR dataset**, in terms of total duration, number of speakers, diversity of diseases, recording conditions, speaker roles, unique medical terms, accents, and ICD-10 codes. 
 
 
-Please cite this paper: **TODO**
+Please cite this paper: [https://arxiv.org/abs/2409.14074](https://arxiv.org/abs/2409.14074)
 
-    @inproceedings{**TODO**,
-      title={**TODO**}, 
-      author={Khai Le-Duc},
-      year={2024},
-      booktitle = {**TODO**},
+    @inproceedings{le2024multimed,
+      title={MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder},
+      author={Le-Duc, Khai and Phan, Phuc and Pham, Tan-Hanh and Tat, Bach Phan and Ngo, Minh-Huong and Hy, Truong-Son},
+      journal={arXiv preprint arXiv:2409.14074},
+      year={2024}
     }
-**TODO** To load labeled data, please refer to our [HuggingFace](https://huggingface.co/datasets/leduckhai/VietMed), [Paperswithcodes](https://paperswithcode.com/dataset/vietmed).
 
-**TODO** For full dataset (labeled data + unlabeled data) and pre-trained models, please refer to [Google Drive](https://drive.google.com/drive/folders/1hsoB_xjWh66glKg3tQaSLm4S1SVPyANP?usp=sharing)
-
-## Limitations:
-
-**TODO** Since this dataset is human-labeled, 1-2 ending/starting words present in the recording might not be present in the transcript. 
-That's the nature of human-labeled dataset, in which humans can't distinguish words that are faster than 1 second.
-In contrast, forced alignment could solve this problem because machines can "listen" words in 10ms-20ms.
-However, forced alignment only learns what it is taught by humans.
-Therefore, no transcript is perfect. We will conduct human-machine collaboration to get "more perfect" transcript in the next paper.
+To load labeled data, please refer to our [HuggingFace](https://huggingface.co/datasets/leduckhai/MultiMed), [Paperswithcodes](https://paperswithcode.com/dataset/multimed).
 
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