ASR Scripts

This project aims to simplify using Kaldi for speech recognition and alignment. It currently works with the ASpIRE pre-trained model, although the scripts can be extended easily to work with different/custom trained models.

Installation

Prerequisites

• Compiled Kaldi instance (instructions)
• ASpIRE chain pre-trained model (download, preparation)
• For displaying the TextGrid alignment files, you will need to install praat.
• For generating TextGrid alignment files, you will need to install the python package for praatIO.

Download scripts

• $ git clone https://github.com/jailuthra/asr
• Place the scripts in kaldi/egs/aspire/s5 directory.

Input audio constraints

Mono PCM wave files, 16-bit sample size, 8KHz sampling rate.

Scripts

• aspire.py: Decodes and aligns the wav files using the pre-trained model, calls the other scripts
• filegen.py: Generates reqd. speaker-id, utterance-id information files using the wav files
• id2phone.py, id2word.py: Convert phone/word ids in ctm output, to actual phones/words
• ctm2tg.py: Convert ctm output to Praat TextGrid files

Usage

1. Create a directory with all your wav files.
2. File naming convention is <speaker_id>_<utterance_id>.wav for example 0001_0001.wav, 0001_0002.wav.
3. Call the aspire script: ./aspire.py <wavdir> <outputdir>.
4. It will generate text transcriptions and alignment files in the output directory.