calculate WER
Hi,
Thanks for your great repo. I have 2 questions:
1- In the Nemo repo is there any implemented code for calculating the WER (word error rate) for a data set & model's transcription? (_i.e._, I mean for example I want to calculate the WER of a trained model on a test set, which I have its ground truth in a text file. So, is there any script in Nemo that I can use it? or I must use other codes such as: [jiwer](https://pypi.org/project/jiwer/))
2- In the [`ASR_CTC_Language_Finetuning`](https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/asr/ASR_CTC_Language_Finetuning.ipynb#scrollTo=iK-RQXEZfq1V) tutorial, if one enables `use_cer` (character error rate) parameter, then the tensor board results will be shown the CER instead of WER? (In other words, I have used the `use_cer = True`, and for example the tensor board showed me the **WER** of the trained model on epoch=31 on validation set is ~ 0.1028. Now I want to know that it is really WER or it is CER? and if it is CER, how I can calculate the WER of the model on my validation or test set?) 
![val_WER](https://user-images.githubusercontent.com/28620609/145693294-daf62515-e6a7-4ff7-a4f8-defdf0eb629b.png)

Best