Updating README.md

rxhmdia · May 31, 2020 · 855c43c · 855c43c
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 ### About the Kinect-WSJ dataset
+Kinect-WSJ is a reverberated, noisy version of the WSJ0-2MIX dataset. Microphones are placed on a linear array with spacing between the devices resembling that of Microsoft Kinect ™, the device used to record the CHiME-5 dataset. This was done so that we could use the real ambient noise captured as part of CHiME-5 dataset. The room impulse responses (RIR) were simulated for a sampling rate of 16,000 Hz.
 
-The Kinect-WSJ dataset is a simulated multi-channel, 
-reverberated version of [wsj0-2mix](../wsj0-mix) with 
-noise samples extracted from non-speech regions of CHiMe5.
+## Path to the dataset
+https://github.com/sunits/Reverberated_WSJ_2MIX/
 
-See the [official repo](https://github.com/sunits/Reverberated_WSJ_2MIX) for more details.
+# Requirements to create Kinect-WSJ dataset
+* wsj_path :  Path to precomputed wsj-2mix dataset. Should contain the folder 2speakers/wav16k/. If you don't have wsj_mix dataset, please create it using the scripts in egs/wsj0_mix
+* chime_path : Path to chime-5 dataset. Should contain the folders train, dev and eval
+* dihard_path : Path to dihard labels. Should contain ```*.lab``` files for the train and dev set
 
-Citation to come.
+# References
+
+```
+@inproceedings{sivasankaran2020,  
+  booktitle = {2020 28th {{European Signal Processing Conference}} ({{EUSIPCO}})},  
+  title={Analyzing the impact of speaker localization errors on speech separation for automatic speech recognition},
+  author={Sunit Sivasankaran and Emmanuel Vincent and Dominique Fohr},
+  year={2021},  
+  month = Jan,  
+}
+```