6 citations · 12 across the 3 of their papers we have counts for
5 papers
Acoustic Scene Classification Using Fusion of Attentive Convolutional Neural Networks for DCASE2019 Challenge
Hossein Zeinali, Lukáš Burget, Jan "Honza'' Černocký
In this report, the Brno University of Technology (BUT) team submissions for Task 1 (Acoustic Scene Classification, ASC) of the DCASE-2019 challenge are described. Also, the analys…
BUT VOiCES 2019 System Description
Hossein Zeinali, Pavel Matějka, Ladislav Mošner +6
This is a description of our effort in VOiCES 2019 Speaker Recognition challenge. All systems in the fixed condition are based on the x-vector paradigm with different features and…
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,…
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…
An Empirical Evaluation of Zero Resource Acoustic Unit Discovery
Chunxi Liu, Jinyi Yang, Ming Sun +7
Acoustic unit discovery (AUD) is a process of automatically identifying a categorical acoustic unit inventory from speech and producing corresponding acoustic unit tokenizations. A…