Weird transcriptions from a fine-tuned model
Hi, 

I fine-tuned a pre-trained French ASR model "stt_fr_conformer_ctc_large" with my own data. And I replaced the tokenizer with my own by `model.change_vocabulary(new_tokenizer_dir=my_own_tokenizer, new_tokenizer_type="bpe")`.

The training was smooth and I got 17% valid WER which is rather good for our dataset, but when I did `transcription=asr_model.transcribe(["example.wav"])` for inference, I got weird transcriptions as below : 
![image](https://user-images.githubusercontent.com/41187612/148400356-a24dfafb-369e-4c53-aa40-3a9ac349cf13.png)
It seems that something changed the alphabet, and here is another example:
![image](https://user-images.githubusercontent.com/41187612/148400928-3c1e21b6-68a7-4781-a226-e47d59afca8c.png)
I looked back into the training log and I found the same thing : 
![image](https://user-images.githubusercontent.com/41187612/148401547-937142cb-f1de-4ab4-8a90-83fa430d37d2.png)

How can I get good transcriptions please ? And is my 17% WER correct ?
Thanks in advance.
