This repository contains code for my blog post

Note: This code uses tensorflow 2.0

Files present:
bare_bones_asr.py:

• code for the neural network explained in the blog
• code for loading sample.wav file and creating its spectrogram
• code for training given neural network with sample.wav and its transcript as input using CTC loss
• code for using trained neural network to predict on an input spectrogram

prefix_beam_search.py:

• code for prefix beam search as explained in the blog
• you can import the function from this file directly and use it on your ctc output

  from prefix_beam_search import prefix_beam_search
  example_ctc_output = None  # get your ctc output from the network
  alphabet = list(ascii_lowercase) + [space_token, end_token, blank_token]  # get your character vocab
  lm = None  # get your language model function
  print(prefix_beam_search(example_ctc, alphabet, blank_token, end_token, space_token, lm=lm))