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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 2019 · eess.ASShow all

6 papers · 2 filters

eess.AS2019

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…

eess.AS2019★ 12 cited

Short-duration Speaker Verification (SdSV) Challenge 2021: the Challenge Evaluation Plan

Hossein Zeinali, Kong Aik Lee, Jahangir Alam +1

This document describes the Short-duration Speaker Verification (SdSV) Challenge 2021. The main goal of the challenge is to evaluate new technologies for text-dependent (TD) and te…

eess.AS2019★ 6 cited

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…

eess.AS2019★ 2 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

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…

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…