Can timestamps and confidence be extracted from a conformer model when used with beam search and LM? 
I have finetuned an english conformer transducer bpe model on romanian and I have a couple of questions after following the tutorials on "Offline ASR" and "ASR confidence estimation":

1. I want to add a kenLM trained model in order to solve some small erros related to missing characters/phonetically transcribed foreign words ("meeting" -> "miting", "business" -> "bisnis"). This is expected because this is how they are pronounced in romanian and the word "meeting" might not appear often in the training set, but I thought that a language model might easily solve this problem. 

However, we would also need a timestamp and confidence estimate per word and from what I understood this is possible only for "greedy decoding without LM". Is it actually possible to extract timestamps/confidence for words for beam search+LM? If it is not yet implemented, how complicated would it be and could you suggest a starting point?

2. From what I understood, transducer decoding is more complicated than CTC, so is there any implementation of confidence+timestamp estimation for CTC models with beam search+LM?  

Thanks in advance!!

