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goodness-of-pronunciation-pipelines-for-oov-problem

Goodness of Pronunciation Pipelines for OOV Removal

https://github.com/agrover112/goodness-of-pronunciation-pipelines-for-oov-problem

Science Score: 67.0%

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    CITATION.cff file
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    .zenodo.json file
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    Found 7 DOI reference(s) in README
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    Links to: arxiv.org, zenodo.org
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Keywords

asr hidden-markov-model kaldi kaldi-asr lexicon-based oov speech speech-recognition
Last synced: 6 months ago · JSON representation ·

Repository

Goodness of Pronunciation Pipelines for OOV Removal

Basic Info
  • Host: GitHub
  • Owner: Agrover112
  • Language: Perl
  • Default Branch: main
  • Homepage:
  • Size: 1.61 MB
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  • Stars: 10
  • Watchers: 2
  • Forks: 3
  • Open Issues: 0
  • Releases: 4
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asr hidden-markov-model kaldi kaldi-asr lexicon-based oov speech speech-recognition
Created over 3 years ago · Last pushed about 3 years ago
Metadata Files
Readme Citation

README.md

Goodness of Pronunciation Pipelines for OOV Problem

DOI

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.

Main Files

  • 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.

Utils:

  • 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 bash ./get_acoustic_metrics.sh wav_file_dir_path transcript_file_dir_path output_folder path

Outputs:

  • gop/: Contains GoP scored outputs and phone level posteriors (IDgopphone_posteriors.txt).
  • lab/posteriors/: Contains IDposteriorinfile.ark from nnet-compute and IDphoneposteriors.ark are posteriors in different format than gop posteriors.
  • lab/: Contains Forced Alignments outputs(phone level and word level .ctm files) IDword.ctm and IDalignmentinfile.txt

image

Citation

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} }

Owner

  • Login: Agrover112
  • Kind: user

Humans trying to understand machines and people.

Citation (CITATION.cff) 

cff-version: 1.1.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Ankit
    given-names: Ankit 
    orcid: https://orcid.org/0000-0003-3724-6605
title: Goodness-of-Pronunciation-Pipelines-for-OOV-Problem
version: new
date-released: 2022-09-14
doi: 10.5281/zenodo.7078826.

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