activity
20182022
most citedBUT VOiCES 2019 System Description

2 citations · 3 across the 3 of their papers we have counts for

collaborators

7 papers

eess.AS20221 cited

Analyzing speaker verification embedding extractors and back-ends under language and channel mismatch

Anna Silnova, Themos Stafylakis, Ladislav Mosner +6

In this paper, we analyze the behavior and performance of speaker embeddings and the back-end scoring model under domain and language mismatch. We present our findings regarding Re…

eess.AS2020

Analysis of the BUT Diarization System for VoxConverse Challenge

Federico Landini, Ondřej Glembek, Pavel Matějka +4

This paper describes the system developed by the BUT team for the fourth track of the VoxCeleb Speaker Recognition Challenge, focusing on diarization on the VoxConverse dataset. Th…

eess.AS20192 cited

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…

eess.AS2019

Factorization of Discriminatively Trained i-vector Extractor for Speaker Recognition

Ondrej Novotny, Oldrich Plchot, Ondrej Glembek +1

In this work, we continue in our research on i-vector extractor for speaker verification (SV) and we optimize its architecture for fast and effective discriminative training. We we…

eess.AS2018

Analysis of DNN Speech Signal Enhancement for Robust Speaker Recognition

Ondrej Novotny, Oldrich Plchot, Ondrej Glembek +2

In this work, we present an analysis of a DNN-based autoencoder for speech enhancement, dereverberation and denoising. The target application is a robust speaker verification (SV)…

eess.AS2018

On the use of DNN Autoencoder for Robust Speaker Recognition

Ondrej Novotny, Oldrich Plchot, Pavel Matejka +1

In this paper, we present an analysis of a DNN-based autoencoder for speech enhancement, dereverberation and denoising. The target application is a robust speaker recognition syste…