Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Gemmeke, Jort F."'
Autor:
van de Loo, Janneke, Gemmeke, Jort F., De Pauw, Guy, Ons, Bart, Daelemans, Walter, Van hamme, Hugo
We present a framework for the induction of semantic frames from utterances in the context of an adaptive command-and-control interface. The system is trained on an individual user's utterances and the corresponding semantic frames representing contr
Externí odkaz:
http://arxiv.org/abs/1901.10680
Autor:
Hershey, Shawn, Chaudhuri, Sourish, Ellis, Daniel P. W., Gemmeke, Jort F., Jansen, Aren, Moore, R. Channing, Plakal, Manoj, Platt, Devin, Saurous, Rif A., Seybold, Bryan, Slaney, Malcolm, Weiss, Ron J., Wilson, Kevin
Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of a dataset of 70M training videos (5.24 million hours) with 30,871 vide
Externí odkaz:
http://arxiv.org/abs/1609.09430
Publikováno v:
In Speech Communication February 2016 76:127-142
Publikováno v:
In Computer Speech & Language July 2014 28(4):997-1017
Publikováno v:
In Speech Communication January 2014 56:49-62
Publikováno v:
In Computer Speech & Language May 2013 27(3):763-779
Autor:
Keronen, Sami, Kallasjoki, Heikki, Remes, Ulpu, Brown, Guy J., Gemmeke, Jort F., Palomäki, Kalle J.
Publikováno v:
In Computer Speech & Language May 2013 27(3):798-819
Publikováno v:
Scopus-Elsevier
ResearcherID
Web of Science
ResearcherID
Web of Science
This paper describes and analyzes several exemplar selection techniques to reduce the number of exemplars that are used in a recently proposed sparse representations-based speech recognition system. Exemplars are labeled acoustic realizations of diff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f00c9cc4b49d6134fe56e8a5d20ccbc0
https://lirias.kuleuven.be/handle/123456789/404360
https://lirias.kuleuven.be/handle/123456789/404360
Akademický článek
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Publikováno v:
2016 IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP); 2016, p5980-5984, 5p