Variational Bayes Factor Analysis for i-Vector Extraction
Machine Learning
2015-11-25 v1
Abstract
In this document we are going to derive the equations needed to implement a Variational Bayes i-vector extractor. This can be used to extract longer i-vectors reducing the risk of overfittig or to adapt an i-vector extractor from a database to another with scarce development data. This work is based on Patrick Kenny's joint factor analysis and Christopher Bishop's variational principal components.
Cite
@article{arxiv.1511.07422,
title = {Variational Bayes Factor Analysis for i-Vector Extraction},
author = {Jesús Villalba},
journal= {arXiv preprint arXiv:1511.07422},
year = {2015}
}
Comments
Technical Report, ViVoLab, I3A, University of Zaragoza, Spain. arXiv admin note: text overlap with arXiv:1511.07318