A proposed pipeline for GoP computation solving OOV problem at Testing time using Vocab/Lexicon expansion techniques. We also provide utilities for extracting the Phoneme posteriors , Word boundaries(alignments), using GoP scores as vectors. The detailed explanation of the pipelines and methods are described in this report.

• run1File.sh : Computes Forced Alignments.
• run1File_posterior.sh : Computation of Acoustic model Posterior Probabilities.
• runAllFiles.sh : Calls necessary files for computation of posteriors and alignment ,GoP computation.
• online_computation.sh: Responsible for the Online/Hybrid pipelne of GoP computation.
• conf/: Configuration files for MFCC, i-vector extractors,etc.
• get_failed_entries.sh : File generates a Lexicon from a text file or dir of text files, along with list of failed entries if any.
• Goodness-of-pronounciation/prop_gop_eqn.py : Contains Python code which calculates GoP scores using posterior and alignment inputs. (Refer to comments in my fork for detailed understanding).

The entire data and exp and lab folders can be found here.

• get_ctm.sh : Get the phone level conversation time mapping files
• get_word_ctm.sh: Get the word level conversation time mapping files.
• get_time.sh : Get the times for ctm files.
• collect_transcripts.sh : Collect and place transcripts from sub-dirs to one file.
• find_oov.sh : A file to find the OOV occurences from 2 databases.
• append_vocab.sh : Append OOV lexicon entries to original Lexicon
• temp_q.sh : File for pre-processing text.
• dict.sh: A modified utils/prepare_dict.sh for Lexicon generation

Entry-point for running the entire pipeline

./get_acoustic_metrics.sh wav_file_dir_path transcript_file_dir_path output_folder path 

• gop/: Contains GoP scored outputs and phone level posteriors (ID_gop_phone_posteriors.txt).
• lab/posteriors/: Contains ID_posterior_infile.ark from nnet-compute and ID_phone_posteriors.ark are posteriors in different format than gop posteriors.
• lab/: Contains Forced Alignments outputs(phone level and word level .ctm files) ID_word_.ctm and ID_alignment_infile.txt

Please cite the both the sources (Arxiv + Zenodo) if any/all of the code is used in your respective research work.

@software{Ankit_Goodness-of-Pronunciation-Pipelines-for-OOV-Problem_2022,
author = {Ankit, Ankit},
doi = {10.5281/zenodo.7078826.},
month = {9},
title = {{Goodness-of-Pronunciation-Pipelines-for-OOV-Problem}},
version = {new},
year = {2022}
}

@misc{https://doi.org/10.48550/arxiv.2209.03787,
  doi = {10.48550/ARXIV.2209.03787}
  url = {https://arxiv.org/abs/2209.03787},
  author = {Grover, Ankit},
  keywords = {Computation and Language (cs.CL), Sound (cs.SD), Audio and Speech Processing (eess.AS), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering},
  title = {Goodness of Pronunciation Pipelines for OOV Problem},
  publisher = {arXiv},
  year = {2022}, 
  copyright = {Creative Commons Attribution Non Commercial Share Alike 4.0 International}
}