10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Joint Speech Enhancement and Speaker Identification Using Monte Carlo Methods

Ciira wa Maina, John MacLaren Walsh

Drexel University, USA

We present an approach to speaker identification using noisy speech observations where the speech enhancement and speaker identification tasks are performed jointly. This is motivated by the belief that human beings perform these tasks jointly and that optimality may be sacrificed if sequential processing is used. We employ a Bayesian approach where the speech features are modeled using a mixture of Gaussians prior. A Gibbs sampler is used to estimate the speech source and the identity of the speaker. Preliminary experimental results are presented comparing our approach to a maximum likelihood approach and demonstrating the ability of our method to both enhance speech and identify speakers.

Full Paper

Bibliographic reference.  Maina, Ciira wa / Walsh, John MacLaren (2009): "Joint speech enhancement and speaker identification using monte carlo methods", In INTERSPEECH-2009, 1375-1378.