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20172022
most citedAcoustic Scene Classification Using Fusion of Attentive Convolutional Neural Networks for DCASE2019 Challenge

6 citations · 27 across the 16 of their papers we have counts for

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6 papers · 1 filter

cs.CL2021

The IWSLT 2021 BUT Speech Translation Systems

Hari Krishna Vydana, Martin Karafi'at, Luk'as Burget +1

The paper describes BUT's English to German offline speech translation(ST) systems developed for IWSLT2021. They are based on jointly trained Automatic Speech Recognition-Machine T…

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…

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…

cs.CL2019

Learning document embeddings along with their uncertainties

Santosh Kesiraju, Oldřich Plchot, Lukáš Burget +1

Majority of the text modelling techniques yield only point-estimates of document embeddings and lack in capturing the uncertainty of the estimates. These uncertainties give a notio…

cs.CL2018

Bayesian Models for Unit Discovery on a Very Low Resource Language

Lucas Ondel, Pierre Godard, Laurent Besacier +7

Developing speech technologies for low-resource languages has become a very active research field over the last decade. Among others, Bayesian models have shown some promising resu…

cs.CL20174 cited

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…