Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Jeroen Zegers"'
Publikováno v:
Procedia CIRP. 109:496-501
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7bcab5d8d12bf269bc10b8955dfcd02a
https://doi.org/10.1016/j.procir.2022.05.284
https://doi.org/10.1016/j.procir.2022.05.284
Autor:
Hugo Van hamme, Jeroen Zegers
Publikováno v:
INTERSPEECH
In recent years there have been many deep learning approaches towards the multi-speaker source separation problem. Most use Long Short-Term Memory - Recurrent Neural Networks (LSTM-RNN) or Convolutional Neural Networks (CNN) to model the sequential b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a880d84e36bd6798467b34c4cb0ec7e6
https://lirias.kuleuven.be/handle/123456789/638714
https://lirias.kuleuven.be/handle/123456789/638714
Publikováno v:
INTERSPEECH
This paper examines the applicability in realistic scenarios of two deep learning based solutions to the overlapping speaker separation problem. Firstly, we present experiments that show that these methods are applicable for a broad range of language
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1bd725a7771e5f343d36bb2165287e9
Autor:
Jeroen Zegers, Hugo Van hamme
Publikováno v:
INTERSPEECH
© 2018 International Speech Communication Association. All rights reserved. With deep learning approaches becoming state-of-the-art in many speech (as well as non-speech) related machine learning tasks, efforts are being taken to delve into the neur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abe6b788a916d35eb352727b94bb5259
https://doi.org/10.21437/interspeech.2018-2082
https://doi.org/10.21437/interspeech.2018-2082
Publikováno v:
ICASSP
© 2018 IEEE. Research in deep learning for multi-speaker source separation has received a boost in the last years. However, most studies are restricted to mixtures of a specific number of speakers, called a specific scenario. While some works includ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d2d01ba0414be1745ec46a5c4a8606a
http://arxiv.org/abs/1808.08095
http://arxiv.org/abs/1808.08095
Autor:
Dries Hulens, Tinne Tuytelaars, Luc Van Gool, Toon Goedemé, Joost Vennekens, Bram Aerts, Luc Van Eycken, Hugo Van hamme, Tom Roussel, Ali Diba, Punarjay Chakravarty, Jeroen Zegers
Publikováno v:
MultiMedia Modeling ISBN: 9783319736020
MMM (1)
MMM (1)
In this paper, we demonstrate a system that automates the process of recording video lectures in classrooms. Through special hard-ware (lecturer and audience facing cameras and microphone arrays), we record multiple points of view of the lecture. Per
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::858d44e1b2ab8243e75b98b4d2c560ad
https://doi.org/10.1007/978-3-319-73603-7_42
https://doi.org/10.1007/978-3-319-73603-7_42
Autor:
Hugo Van hamme, Jeroen Zegers
Publikováno v:
INTERSPEECH
Copyright © 2017 ISCA. Lately there have been novel developments in deep learning towards solving the cocktail party problem. Initial results are very promising and allow for more research in the domain. One technique that has not yet been explored
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6648365af2fe40e3dc5d03b4bc4498bf
http://arxiv.org/abs/1708.08740
http://arxiv.org/abs/1708.08740
Autor:
Hugo Van hamme, Jeroen Zegers
Publikováno v:
INTERSPEECH
Non-negative Matrix Factorization (NMF) has already been applied to learn speaker characterizations from single or non-simultaneous speech for speaker recognition applications. It is also known for its good performance in (blind) source separation fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e586f4d1061181875c7555221e19e38
Publikováno v:
ICMI
© 2016 ACM. In this work, we show how to co-Train a classifier for active speaker detection using audio-visual data. First, audio Voice Activity Detection (VAD) is used to train a personalized video-based active speaker classifier in a weakly superv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::136a0c2c9aa3a65af6f3f3c17258079d
https://lirias.kuleuven.be/handle/123456789/559697
https://lirias.kuleuven.be/handle/123456789/559697