Novel Methods for Query Selection and Query Combination in Query-By-Example Spoken Term Detection

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Novel Methods for Query Selection and Query Combination in Query-By-Example Spoken Term Detection

Popis výsledku v původním jazyce

Query-by-example (QbE) spoken term detection (STD) is necessary for low-resource scenarios where training material is hardly available and word-based speech recognition systems cannot be employed. We present two novel contributions to QbE STD: the firstintroduces several criteria to select the optimal example used as query throughout the search system. The second presents a novel feature level example combination to construct a more robust query used during the search. Experiments, tested on with-in language and cross-lingual QbE STD setups, show a significant improvement when the query is selected according to an optimal criterion over when the query is selected randomly for both setups and a significant improvement when several examples are combinedto build the input query for the search system compared with the use of the single best example. They also show comparable performance to that of a stateof- the-art acoustic keyword spotting system.

Název v anglickém jazyce

Novel Methods for Query Selection and Query Combination in Query-By-Example Spoken Term Detection

Popis výsledku anglicky

Query-by-example (QbE) spoken term detection (STD) is necessary for low-resource scenarios where training material is hardly available and word-based speech recognition systems cannot be employed. We present two novel contributions to QbE STD: the firstintroduces several criteria to select the optimal example used as query throughout the search system. The second presents a novel feature level example combination to construct a more robust query used during the search. Experiments, tested on with-in language and cross-lingual QbE STD setups, show a significant improvement when the query is selected according to an optimal criterion over when the query is selected randomly for both setups and a significant improvement when several examples are combinedto build the input query for the search system compared with the use of the single best example. They also show comparable performance to that of a stateof- the-art acoustic keyword spotting system.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2010

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the ACM Multimedia 2010 International Conference

ISBN

978-1-60558-933-6

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

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Název nakladatele

Association for Computing Machinery

Místo vydání

Florencie

Místo konání akce

Florencie

Datum konání akce

25. 10. 2010

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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