19 citations · 19 across the 1 of their papers we have counts for
2 papers
cs.CV2019
Self-supervised speaker embeddings
Themos Stafylakis, Johan Rohdin, Oldrich Plchot +2
Contrary to i-vectors, speaker embeddings such as x-vectors are incapable of leveraging unlabelled utterances, due to the classification loss over training speakers. In this paper,…
eess.AS2017
End-to-end DNN Based Speaker Recognition Inspired by i-vector and PLDA
Johan Rohdin, Anna Silnova, Mireia Diez +3
Recently several end-to-end speaker verification systems based on deep neural networks (DNNs) have been proposed. These systems have been proven to be competitive for text-dependen…