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20172022
most citedBUT System Description for DIHARD Speech Diarization Challenge 2019

19 citations · 20 across the 2 of their papers we have counts for

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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.AS2021

Speaker embeddings by modeling channel-wise correlations

Themos Stafylakis, Johan Rohdin, Lukas Burget

Speaker embeddings extracted with deep 2D convolutional neural networks are typically modeled as projections of first and second order statistics of channel-frequency pairs onto a…

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.AS2020

Probabilistic embeddings for speaker diarization

Anna Silnova, Niko Brümmer, Johan Rohdin +2

Speaker embeddings (x-vectors) extracted from very short segments of speech have recently been shown to give competitive performance in speaker diarization. We generalize this reci…

eess.AS2020

BUT System for the Second DIHARD Speech Diarization Challenge

Federico Landini, Shuai Wang, Mireia Diez +9

This paper describes the winning systems developed by the BUT team for the four tracks of the Second DIHARD Speech Diarization Challenge. For tracks 1 and 2 the systems were mainly…

eess.AS201919 cited

BUT System Description for DIHARD Speech Diarization Challenge 2019

Federico Landini, Shuai Wang, Mireia Diez +8

This paper describes the systems developed by the BUT team for the four tracks of the second DIHARD speech diarization challenge. For tracks 1 and 2 the systems were based on perfo…