Fast Approximate Spoken Term Detection from Sequence of Phonemes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F08%3APU80187" target="_blank" >RIV/00216305:26230/08:PU80187 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Fast Approximate Spoken Term Detection from Sequence of Phonemes
Original language description
We investigate the detection of spoken terms in conversa-<br> tional speech using phoneme recognition with the objective<br> of achieving smaller index size as well as faster search speed.<br> Speech is processed and indexed as a sequence of one best<br>phoneme sequence. We propose the use of a probabilistic<br> pronunciation model for the search term to compensate for<br> the errors in the recognition of phonemes. This model is de-<br> rived using the pronunciation of the word and the phoneme<br> confusion matrix. Experiments are performed on the con-<br> versational telephone speech database distributed by NIST<br> for the 2006 spoken term detection. We achieve about 1500<br> times smaller index size and 14 times faster search speed<br> compared tothe system using phoneme lattices, at the cost<br> of relatively lower detection performance.
Czech name
Fast Approximate Spoken Term Detection from Sequence of Phonemes
Czech description
We investigate the detection of spoken terms in conversa-<br>tional speech using phoneme recognition with the objective<br>of achieving smaller index size as well as faster search speed.<br>Speech is processed and indexed as a sequence of one best<br>phoneme sequence. We propose the use of a probabilistic<br>pronunciation model for the search term to compensate for<br>the errors in the recognition of phonemes. This model is de-<br>rived using the pronunciation of the word and the phoneme<br>confusion matrix. Experiments are performed on the con-<br>versational telephone speech database distributed by NIST<br>for the 2006 spoken term detection. We achieve about 1500<br>times smaller index size and 14 times faster search speed<br>compared to the system using phoneme lattices, at the cost<br>of relatively lower detection performance.<br><br>
Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
The 31st Annual International ACM SIGIR Conference 20-24 July 2008, Singapore
ISBN
978-90-365-2697-5
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
Association for Computing Machinery
Place of publication
Singapore
Event location
Singapur
Event date
Jul 20, 2008
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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