Result Details

Recurrent neural network based language model

MIKOLOV, T.; KARAFIÁT, M.; BURGET, L.; ČERNOCKÝ, J.; KHUDANPUR, S. Recurrent neural network based language model. Proceedings of the 11th Annual Conference of the International Speech Communication Association (INTERSPEECH 2010). Proceedings of Interspeech. Makuhari, Chiba: International Speech Communication Association, 2010. no. 9, p. 1045-1048. ISBN: 978-1-61782-123-3. ISSN: 1990-9772.
Type
conference paper
Language
English
Authors
Mikolov Tomáš, Ing., Ph.D., DCGM (FIT)
Karafiát Martin, Ing., Ph.D., DCGM (FIT)
Burget Lukáš, doc. Ing., Ph.D., DCGM (FIT)
Černocký Jan, prof. Dr. Ing., DCGM (FIT)
Khudanpur Sanjeev
Abstract

This paper is on new application to speech recognition, the recurrent neural network based language model (RNN LM).

Keywords

language modeling, recurrent neural networks, speech recognition

URL
Annotation

A new recurrent neural network based language model (RNN LM) with applications to speech recognition is presented. Results indicate that it is possible to obtain around 50% reduction of perplexity by using mixture of several RNN LMs, compared to a state of the art backoff language model. Speech recognition experiments show around 18% reduction of word error rate on the Wall Street Journal task when comparing models trained on the same amount of data, and around 5% on the much harder NIST RT05 task, even when the backoff model is trained on much more data than the RNN LM. We provide ample empirical evidence to suggest that connectionist language models are superior to standard n-gram techniques, except their high computational (training) complexity.

Published
2010
Pages
1045–1048
Journal
Proceedings of Interspeech, vol. 2010, no. 9, ISSN 1990-9772
Proceedings
Proceedings of the 11th Annual Conference of the International Speech Communication Association (INTERSPEECH 2010)
Conference
Interspeech Conference
ISBN
978-1-61782-123-3
Publisher
International Speech Communication Association
Place
Makuhari, Chiba
BibTeX 
@inproceedings{BUT35937,
  author="Tomáš {Mikolov} and Martin {Karafiát} and Lukáš {Burget} and Jan {Černocký} and Sanjeev {Khudanpur}",
  title="Recurrent neural network based language model",
  booktitle="Proceedings of the 11th Annual Conference of the International Speech Communication Association (INTERSPEECH 2010)",
  year="2010",
  journal="Proceedings of Interspeech",
  volume="2010",
  number="9",
  pages="1045--1048",
  publisher="International Speech Communication Association",
  address="Makuhari, Chiba",
  isbn="978-1-61782-123-3",
  issn="1990-9772",
  url="http://www.fit.vutbr.cz/research/groups/speech/publi/2010/mikolov_interspeech2010_IS100722.pdf"
}
Projects
DIRAC - Detection and Identification of Rare Audio-visual Cues, MŠMT, Šestý rámcový program Evropského společenství pro výzkum, technický rozvoj a demonstrační činnosti, 027787, start: 2006-01-01, end: 2010-12-31, completed
Overcoming the language barrier complicating investigation into financing terrorism and serious financial crimes, MV, Program bezpečnostního výzkumu, VD20072010B16, start: 2007-08-01, end: 2010-12-31, completed
Recognition and presentation of multimedia data, BUT, Vnitřní projekty VUT, FIT-S-10-2, 2010, start: 2010-04-01, end: 2010-12-31, completed
Security-Oriented Research in Information Technology, MŠMT, Institucionální prostředky SR ČR (např. VZ, VC), MSM0021630528, start: 2007-01-01, end: 2013-12-31, running
Speech Recognition under Real-World Conditions, GACR, Standardní projekty, GA102/08/0707, start: 2008-01-01, end: 2011-12-31, completed
Research groups
Speech Data Mining Research Group BUT Speech@FIT (RG SPEECH)
Departments
Department of Computer Graphics and Multimedia (DCGM)
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