KenLM with ASR
Hi, I'm fine tuning Quartznet (character model) and CTC-Conformer (BPE model) on new language and the results are good. Then I use KenLM with both. I have some question:
1. When I download and see "3-gram.pruned.1e-7.arpa" file in [this tutorial](https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/asr/Offline_ASR.ipynb#scrollTo=-0Sk0C9-LmAR), I recognize that this file for word level, but Quartznet is character level, but It work well. Can you explain how it work ?
2. I train KenLM for CTC-Conformer (BPE model) according to [asr language model tutorial](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/asr/asr_language_modeling.html), and the training was successful. But when I apply it with beamsearch to CTC-Conformer, it gives me irrelevant results(wer upto 40%), while using greedy search wer ~ 9%. I don't know what makes it not work. Can you give me some advice?
Thank you!
