fastivector

This repository contains the code for fast ivector model training and ivector extraction in Kaldi using randomized SVD.

Theoretical details

The theory behind this technique is described in this paper. The randomized SVD algorithm we used is based on the proto algorithm in this paper.

Using the code and scripts

Compilation

1. This code is based on Kaldi, so you will need to install and compile it first.

2. Copy the contents of src folder to the src folder of your Kaldi installation.

3. Compile the code:

   # Navigate to <kaldi-root>/src
   cd ~/kaldi-trunk/src
   
   # Compile fastivector
   cd fastivector
   make depend
   make
   
   # Compile fastivectorbin
   cd ../fastivectorbin
   make depend
   make

Scripts

Scripts are provided for both a diagonal covariance and a full covariance version of the model. Just copy the contents of the required version inside the steps directory of the relevant egs directory (for example : <kaldi-root>/egs/wsj/s5/steps).

Then, the code can be executed by calling the top-level training/extraction script.

cd ~/kaldi-trunk/egs/wsj/s5
# Training
bash steps/fastivec_diag/train_fastivec_diag.sh --nj 4 data/train_si284 512 exp/fastivec_diag_512
# Extraction
bash steps/fastivec_diag/extract_ivec.sh --nj 4 data/test_eval92 exp/fastivec_diag_512  exp/fastivec_diag_512/ivectors_test_eval92