2 papers
cs.LG2020
An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam +2
In this contribution, we augment the metric learning setting by introducing a parametric pseudo-distance, trained jointly with the encoder. Several interpretations are thus drawn f…
eess.AS2018
Generative Adversarial Speaker Embedding Networks for Domain Robust End-to-End Speaker Verification
Gautam Bhattacharya, Joao Monteiro, Jahangir Alam +1
This article presents a novel approach for learning domain-invariant speaker embeddings using Generative Adversarial Networks. The main idea is to confuse a domain discriminator so…