About BK-tree you mentioned in the paper

[JackSnowWolf]

Hi!

You mentioned that you used BK-tree data structure to improve efficiency. Could you some how explain that how you use that data structure? I felt confused after I didn't find any details of BK-tree in your training code or inference code.

Thanks!

[githubharald]

this decoding strategy is pretty simple:

1. find approximation for recognized word using best path decoding
2. then, find the words (given as a dictionary) most similar to the approximation and put it in list of candidates (this can be done using a BK tree)
3. compute the probability (loss) of all possible candidates
4. return best scoring word

Python implementation see: https://github.com/githubharald/CTCDecoder/blob/master/src/LexiconSearch.py

[JackSnowWolf]

@githubharald Thank you very much!