Comparison of methods for language-dependent and language-independent query-by-example spoken term detection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F12%3APU101882" target="_blank" >RIV/00216305:26230/12:PU101882 - isvavai.cz</a>
Result on the web
<a href="http://dl.acm.org/citation.cfm?id=2328971&CFID=187707319&CFTOKEN=67886685" target="_blank" >http://dl.acm.org/citation.cfm?id=2328971&CFID=187707319&CFTOKEN=67886685</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2328967.2328971" target="_blank" >10.1145/2328967.2328971</a>

Result language
angličtina
Original language name
Comparison of methods for language-dependent and language-independent query-by-example spoken term detection
Original language description
This article investigates query-by-example (QbE) spoken term detection (STD), in which the query is not entered as text, but selected in speech data or spoken. Two feature extractors based on neural networks (NN) are introduced: the first producing phone-state posteriors and the second making use of a compressive NN layer. They are combined with three different QbE detectors: while the Gaussian mixture model/hidden Markov model (GMM/HMM) and dynamic time warping (DTW) both work on continuous feature vectors, the third one, based on weighted finite-state transducers (WFST), processes phone lattices.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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