Update README.md

README.md

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 # HypothesesParadise
 This repo releases the Robust HyPoradise dataset in paper "Large Language Models are Efficient Learners of Noise-Robust Speech Recognition."
 
+NEW (Apr-18): We have released the training data, which follows the same format as valid/test data. 
+Considering the file size, the uploaded training data does not contain the speech features (vast size).
+Alternatively, we have provided a script named `add_speech_feats_to_train_data.py` to generate them from raw speech (.wav).
+You need to specify the raw speech path from utterance id in the script.
+Here are the available speech data: [CHiME-4](https://entuedu-my.sharepoint.com/:f:/g/personal/yuchen005_e_ntu_edu_sg/EuLgMQbjrIJHk7dKPkjcDMIB4SYgXKKP8VBxyiZk3qgdgA),
+[VB-DEMAND](https://datashare.ed.ac.uk/handle/10283/2791), [LS-FreeSound](https://github.com/archiki/Robust-E2E-ASR), [NOIZEUS](https://ecs.utdallas.edu/loizou/speech/noizeus/).
+
 If you consider this work would be related or useful for your research, please kindly consider to cite the work in ICLR 2024. Thank you.
 
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