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Out-of-Vocabulary Word Recovery Using FST-Based Subword Unit Clustering in a Hybrid ASR System

EGOROVA Ekaterina and BURGET Lukáš. Out-of-Vocabulary Word Recovery Using FST-Based Subword Unit Clustering in a Hybrid ASR System. In: Proceedings of ICASSP 2018. Calgary: IEEE Signal Processing Society, 2018, pp. 5919-5923. ISBN 978-1-5386-4658-8.
Czech title
Doplňování slov mimo slovník pomocí shlukování pod-slovních jednotek založeného na FST v hybridním ASR systému
Type
conference paper
Language
english
Authors
URL
Keywords
Out-of-vocabulary Words, Robust ASR
Abstract
The paper presents a new approach to extracting useful information from out-of-vocabulary (OOV) speech regions in ASR system output. The system makes use of a hybrid decoding network with both words and sub-word units. In the decoded lattices, candidates for OOV regions are identified as sub-graphs of sub-word units. To facilitate OOV word recovery, we search for recurring OOVs by clustering the detected candidate OOVs. The metrics for clustering is based on a comparison of the sub-graphs corresponding to the OOV candidates. The proposed method discovers repeating outof- vocabulary words and finds their graphemic representation more robustly than more conventional techniques taking into account only one best sub-word string hypotheses.
Published
2018
Pages
5919-5923
Proceedings
Proceedings of ICASSP 2018
Conference
IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, CA
ISBN
978-1-5386-4658-8
Publisher
IEEE Signal Processing Society
Place
Calgary, CA
DOI
BibTeX
@INPROCEEDINGS{FITPUB11725,
   author = "Ekaterina Egorova and Luk\'{a}\v{s} Burget",
   title = "Out-of-Vocabulary Word Recovery Using FST-Based Subword Unit Clustering in a Hybrid ASR System",
   pages = "5919--5923",
   booktitle = "Proceedings of ICASSP 2018",
   year = 2018,
   location = "Calgary, CA",
   publisher = "IEEE Signal Processing Society",
   ISBN = "978-1-5386-4658-8",
   doi = "10.1109/ICASSP.2018.8462221",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11725"
}
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