Compact Speaker Embedding: lrx-Vector

Munir Georges, Jonathan Huang, Tobias Bocklet
2020 Interspeech 2020  
Deep neural networks (DNN) have recently been widely used in speaker recognition systems, achieving state-of-the-art performance on various benchmarks. The x-vector architecture is especially popular in this research community, due to its excellent performance and manageable computational complexity. In this paper, we present the lrx-vector system, which is the low-rank factorized version of the x-vector embedding network. The primary objective of this topology is to further reduce the memory
more » ... quirement of the speaker recognition system. We discuss the deployment of knowledge distillation for training the lrx-vector system and compare against low-rank factorization with SVD. On the VOiCES 2019 far-field corpus we were able to reduce the weights by 28% compared to the full-rank x-vector system while keeping the recognition rate constant (1.83 % EER).
doi:10.21437/interspeech.2020-2106 dblp:conf/interspeech/GeorgesHB20 fatcat:eopoener7ndirgm6kgiuixzwam