activity
20172024
most citedConvolutional Neural Networks and x-vector Embedding for DCASE2018 Acoustic Scene Classification Challenge

44 citations · 100 across the 34 of their papers we have counts for

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Showing 2020Show all

9 papers · 1 filter

eess.AS2020★ 1 cited

Bayesian HMM clustering of x-vector sequences (VBx) in speaker diarization: theory, implementation and analysis on standard tasks

Federico Landini, Ján Profant, Mireia Diez +1

The recently proposed VBx diarization method uses a Bayesian hidden Markov model to find speaker clusters in a sequence of x-vectors. In this work we perform an extensive compariso…

eess.AS2020

Integration of variational autoencoder and spatial clustering for adaptive multi-channel neural speech separation

Katerina Zmolikova, Marc Delcroix, Lukáš Burget +2

In this paper, we propose a method combining variational autoencoder model of speech with a spatial clustering approach for multi-channel speech separation. The advantage of integr…

cs.CL2020

Text Augmentation for Language Models in High Error Recognition Scenario

Karel Beneš, Lukáš Burget

We examine the effect of data augmentation for training of language models for speech recognition. We compare augmentation based on global error statistics with one based on per-wo…

eess.AS2020★ 5 cited

A Hierarchical Subspace Model for Language-Attuned Acoustic Unit Discovery

Bolaji Yusuf, Lucas Ondel, Lukas Burget +2

In this work, we propose a hierarchical subspace model for acoustic unit discovery. In this approach, we frame the task as one of learning embeddings on a low-dimensional phonetic…

cs.CL2020

A Technical Report: BUT Speech Translation Systems

Hari Krishna Vydana, Lukas Burget, Jan Cernocky

The paper describes the BUT's speech translation systems. The systems are EnglishGerman offline speech translation systems. The systems are based on our previous w…

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…