6 citations · 9 across the 4 of their papers we have counts for
12 papers
Jointly Trained Transformers models for Spoken Language Translation
Hari Krishna Vydana, Martin Karafi'at, Katerina Zmolikova +2
Conventional spoken language translation (SLT) systems are pipeline based systems, where we have an Automatic Speech Recognition (ASR) system to convert the modality of source from…
BUT Opensat 2019 Speech Recognition System
Martin Karafiát, Murali Karthick Baskar, Igor Szöke +3
The paper describes the BUT Automatic Speech Recognition (ASR) systems submitted for OpenSAT evaluations under two domain categories such as low resourced languages and public safe…
A Multi Purpose and Large Scale Speech Corpus in Persian and English for Speaker and Speech Recognition: the DeepMine Database
Hossein Zeinali, Lukáš Burget, Jan "Honza'' Černocký
DeepMine is a speech database in Persian and English designed to build and evaluate text-dependent, text-prompted, and text-independent speaker verification, as well as Persian spe…
Detecting Spoofing Attacks Using VGG and SincNet: BUT-Omilia Submission to ASVspoof 2019 Challenge
Hossein Zeinali, Themos Stafylakis, Georgia Athanasopoulou +4
In this paper, we present the system description of the joint efforts of Brno University of Technology (BUT) and Omilia -- Conversational Intelligence for the ASVSpoof2019 Spoofing…
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…
Semi-supervised Sequence-to-sequence ASR using Unpaired Speech and Text
Murali Karthick Baskar, Shinji Watanabe, Ramon Astudillo +3
Sequence-to-sequence automatic speech recognition (ASR) models require large quantities of data to attain high performance. For this reason, there has been a recent surge in intere…