Conference paper

SZŐKE Igor, FAPŠO Michal, BURGET Lukáš and ČERNOCKÝ Jan. Hybrid word-subword decoding for spoken term detection. In: Proc. SSCS 2008: Speech search workshop at SIGIR. Singapore: Association for Computing Machinery, 2008, p. 4. ISBN 978-90-365-2697-5.
Publication language:english
Original title:Hybrid word-subword decoding for spoken term detection
Title (cs):Hybridní slovní a podslovní dekóodování pro detekci klíčových frází v řeči
Proceedings:Proc. SSCS 2008: Speech search workshop at SIGIR
Conference:31st International ACM SIGIR Conference
Place:Singapore, SG
Publisher:Association for Computing Machinery
spoken term detection
The paper is hybrid word-subword decoding for spoken term detection
This paper deals with a hybrid word-subword recognition system for spoken term detection. The decoding is driven by a hybrid recognition network and the decoder directly produces hybrid word-subword lattices. One phone and two multigram models were tested to represent sub-word units. The systems were evaluated in terms of spoken term detection accuracy and the size of index. We concluded that the best subword model for hybrid word-subword recognition is the multigram model trained on the word recognizer vocabulary. We achieved an improvement in word recognition accuracy, and in spoken term detection accuracy when in-vocabulary and out-of-vocabulary terms are searched separately. Spoken term detection accuracy with the full (in-vocabulary and out-of-vocabulary) term set was slightly worse but the required index size was significantly reduced.
   author = {Igor Sz{\H{o}}ke and Michal Fap{\v{s}}o and
	Luk{\'{a}}{\v{s}} Burget and Jan
   title = {Hybrid word-subword decoding for spoken term
   pages = {4},
   booktitle = {Proc. SSCS 2008: Speech search workshop at SIGIR},
   year = {2008},
   location = {Singapore, SG},
   publisher = {Association for Computing Machinery},
   ISBN = {978-90-365-2697-5},
   language = {english},
   url = {}

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