| # 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 | |