8000 GitHub - pavs315/Kaldi-Scripts: Scripts to train a simple HMM-GMM ASR model in Kaldi toolkit
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Instructions for making a simple HMM-GMM ASR model in Kaldi

Train and Test Data

Audio Data

Create Test and Train folders in the Audio folder and store the audio data.

Acoustic and Language Data

Create Test and Train folders in the Data folder with the following files in each folder.

  • spk2gender <speakerID><gender>
  • wav.scp <uterranceID> <full_path_to_audio_file>
  • text <uterranceID> <text_transcription>
  • utt2spk <uterranceID> <speakerID>

Create a folder local with the following file and a subfolder dict -

  • corpus.txt <text_transcription>

Create the follwing files in dict

 sil
 spn
  • optional_silence.txt
sil

Utils and Config

Copy the utils and steps folders from Kaldi-Master/egs/wsj/s5 into the model directory

Scoring script

Copy score.sh from Kaldi-Master/egs/voxforge/s5/local into the local folder of the model directory.

Config files

Create a folder conf in the model directory and copy the decode.config and mfcc.conf files from this repository.

Running the Model

Copy the files cmd.sh, path.sh and run.sh to the project directory

Run ./run.sh

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