Conference paper

EGOROVA Ekaterina. Multi-task Neural Networks For Speech Recognition. In: Proceedings of the 20th Student Conference, EEICT 2014. Brno: Brno University of Technology, 2014, pp. 24-26. ISBN 978-80-214-4923-7. Available from: http://www.feec.vutbr.cz/EEICT/wp-content/uploads/2014/04/2014-sbornik-mgr.pdf
Publication language:english
Original title:Multi-task Neural Networks For Speech Recognition
Title (cs):Víceúkolové trénování neuronových sítí pro rozpoznávání řeči
Pages:24-26
Proceedings:Proceedings of the 20th Student Conference, EEICT 2014
Conference:Student EEICT 2014
Series:Volume 2
Place:Brno, CZ
Year:2014
URL:http://www.feec.vutbr.cz/EEICT/wp-content/uploads/2014/04/2014-sbornik-mgr.pdf
ISBN:978-80-214-4923-7
Publisher:Brno University of Technology
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2014/egorova_eeict2014_p24_26.pdf [PDF]
Keywords
Speech recognition, neural networks, deep neural networks, multi-task neural networks.
Annotation
Článek pojednává o víceúkolovém trénování neuronových sítí pro rozpoznávání řeči.
Abstract
The article covers experiments on TIMIT database exploring the possibility of using multitask neural networks for speech recognition. Multi-task neural networks are deep neural networks solving several different classification tasks simultaneously. The secondary tasks chosen for the experiments are gender, context, articulatory characteristics and a fusion of some of them. The experiments show that addition of such tasks can enhance the learning and improve recognition accuracy.
BibTeX:
@INPROCEEDINGS{
   author = {Ekaterina Egorova},
   title = {Multi-task Neural Networks For Speech Recognition},
   pages = {24--26},
   booktitle = {Proceedings of the 20th Student Conference, EEICT 2014},
   series = {Volume 2},
   year = {2014},
   location = {Brno, CZ},
   publisher = {Brno University of Technology},
   ISBN = {978-80-214-4923-7},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=10629}
}

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