Python3.6
Pytorch
python-dateutil
easydict
pandas
torchfile
gdown
pickle

Listener Position = LP
Source Position = SP
Room Dimension = RD
Reverberation Time = T60
Correction = CRR

CRR = 0.1 if 0.5
   
    <0.6
CRR = 0.2 if T60>0.6
CRR = 0 otherwise

Embedding = ([LP_X,LP_Y,LP_Z,SP_X,SP_y,SP_Z,RD_X,RD_Y,RD_Z,(T60+CRR)] /5) + 1

   

source download_generate.sh

 python3 example1.py

python3 main.py --cfg cfg/RIR_eval.yml --gpu 0

Room Dimension X --> 8m to 11m
Room Dimesnion Y --> 6m to 8m
Room Dimension Z --> 2.5m to 3.5m
Listener Position --> Any position within the room
Speaker Position --> Any position within the room
Reverberation time --> 0.2s to 0.7s

source download_data.sh

python3 main.py --cfg cfg/RIR_s1.yml --gpu 0,1

@misc{ratnarajah2021fastrir,
      title={FAST-RIR: Fast neural diffuse room impulse response generator}, 
      author={Anton Ratnarajah and Shi-Xiong Zhang and Meng Yu and Zhenyu Tang and Dinesh Manocha and Dong Yu},
      year={2021},
      eprint={2110.04057},
      archivePrefix={arXiv},
      primaryClass={cs.SD}
}

@inproceedings{han2017stackgan,
Author = {Han Zhang and Tao Xu and Hongsheng Li and Shaoting Zhang and Xiaogang Wang and Xiaolei Huang and Dimitris Metaxas},
Title = {StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks},
Year = {2017},
booktitle = {{ICCV}},
}

@inproceedings{9052932,
  author={Z. {Tang} and L. {Chen} and B. {Wu} and D. {Yu} and D. {Manocha}},  
  booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},  
  title={Improving Reverberant Speech Training Using Diffuse Acoustic Simulation},   
  year={2020},  
  volume={},  
  number={},  
  pages={6969-6973},
}