Result Details

OOV detection in LVCSR using neural networks

KOMBRINK, S. OOV detection in LVCSR using neural networks. Proc. STUDENT EEICT 2008. Brno: Faculty of Electrical Engineering and Communication BUT, 2008. p. 1-3. ISBN: 978-80-214-3617-6.
Type
conference paper
Language
English
Authors
Kombrink Stefan, Dipl.-Linguist.
Abstract

The work is on OOV detection in LVCSR using neural networks

Keywords

speech recognition

URL
Annotation

Confidence measures and classifying techniques are widely used for the recognition error detection task in LVCSR (Large Vocabulary Continuous Speech Recognition). But in many recognition scenarios the amount of words not included in the dictionary (e.g. real names, neologisms) lead to so-called OOV (Out Of Vocabulary) errors which increase the WER (Word Error Rate) even more. The hereby described work acknowledges and investigates further improvements of an OOV detection task performed by combining strong and weak phone posterior features using neural networks based on [ICASSP08] and the use of phone context.

Published
2008
Pages
1–3
Proceedings
Proc. STUDENT EEICT 2008
Conference
Student EEICT 2008
ISBN
978-80-214-3617-6
Publisher
Faculty of Electrical Engineering and Communication BUT
Place
Brno
BibTeX 
@inproceedings{BUT33883,
  author="Stefan {Kombrink}",
  title="OOV detection in LVCSR using neural networks",
  booktitle="Proc. STUDENT EEICT 2008",
  year="2008",
  pages="1--3",
  publisher="Faculty of Electrical Engineering and Communication BUT",
  address="Brno",
  isbn="978-80-214-3617-6",
  url="http://www.fit.vutbr.cz/research/groups/speech/publi/2008/kombrink_eeict.pdf"
}
Projects
Security-Oriented Research in Information Technology, MŠMT, Institucionální prostředky SR ČR (např. VZ, VC), MSM0021630528, start: 2007-01-01, end: 2013-12-31, running
Research groups
Speech Data Mining Research Group BUT Speech@FIT (RG SPEECH)
Departments
Department of Computer Graphics and Multimedia (DCGM)
Back to top