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# This module is from [WeNet](https://github.com/wenet-e2e/wenet). | |
# ## Citations | |
# ```bibtex | |
# @inproceedings{yao2021wenet, | |
# title={WeNet: Production oriented Streaming and Non-streaming End-to-End Speech Recognition Toolkit}, | |
# author={Yao, Zhuoyuan and Wu, Di and Wang, Xiong and Zhang, Binbin and Yu, Fan and Yang, Chao and Peng, Zhendong and Chen, Xiaoyu and Xie, Lei and Lei, Xin}, | |
# booktitle={Proc. Interspeech}, | |
# year={2021}, | |
# address={Brno, Czech Republic }, | |
# organization={IEEE} | |
# } | |
# @article{zhang2022wenet, | |
# title={WeNet 2.0: More Productive End-to-End Speech Recognition Toolkit}, | |
# author={Zhang, Binbin and Wu, Di and Peng, Zhendong and Song, Xingchen and Yao, Zhuoyuan and Lv, Hang and Xie, Lei and Yang, Chao and Pan, Fuping and Niu, Jianwei}, | |
# journal={arXiv preprint arXiv:2203.15455}, | |
# year={2022} | |
# } | |
# | |
import torch | |
class GlobalCMVN(torch.nn.Module): | |
def __init__(self, mean: torch.Tensor, istd: torch.Tensor, norm_var: bool = True): | |
""" | |
Args: | |
mean (torch.Tensor): mean stats | |
istd (torch.Tensor): inverse std, std which is 1.0 / std | |
""" | |
super().__init__() | |
assert mean.shape == istd.shape | |
self.norm_var = norm_var | |
# The buffer can be accessed from this module using self.mean | |
self.register_buffer("mean", mean) | |
self.register_buffer("istd", istd) | |
def forward(self, x: torch.Tensor): | |
""" | |
Args: | |
x (torch.Tensor): (batch, max_len, feat_dim) | |
Returns: | |
(torch.Tensor): normalized feature | |
""" | |
x = x - self.mean | |
if self.norm_var: | |
x = x * self.istd | |
return x | |