Two-Layer Semantic Entity Detection and Utterance Validation for Spoken Dialogue Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F14%3A43922769" target="_blank" >RIV/49777513:23520/14:43922769 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/content/pdf/10.1007%2F978-3-319-10816-2_68.pdf" target="_blank" >http://link.springer.com/content/pdf/10.1007%2F978-3-319-10816-2_68.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-10816-2_68" target="_blank" >10.1007/978-3-319-10816-2_68</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Two-Layer Semantic Entity Detection and Utterance Validation for Spoken Dialogue Systems

Popis výsledku v původním jazyce

In this paper we present a novel method for semantic entity detection in a limited domain for spoken language understanding. The target domain of this method is a dialogue system for an interactive training of air traffic controllers (ATC). The method comprises of two layers of detection. First layer uses formerly proposed method for semantic entity detection to extract domain-dependent set of semantic entities. This semantic entities are modelled using context-free grammars. To detect mispronounced words or words which do not comply with the ATC radio-telephony rules we use the second layer of semantic entity detection. Together with that, we assign a semantic meaning to the utterance. We also discuss the possibility of using this approach for semantic-based correction of an utterance. The experiments were performed on transcribed data as well as on an output from speech recognizer.

Název v anglickém jazyce

Two-Layer Semantic Entity Detection and Utterance Validation for Spoken Dialogue Systems

Popis výsledku anglicky

In this paper we present a novel method for semantic entity detection in a limited domain for spoken language understanding. The target domain of this method is a dialogue system for an interactive training of air traffic controllers (ATC). The method comprises of two layers of detection. First layer uses formerly proposed method for semantic entity detection to extract domain-dependent set of semantic entities. This semantic entities are modelled using context-free grammars. To detect mispronounced words or words which do not comply with the ATC radio-telephony rules we use the second layer of semantic entity detection. Together with that, we assign a semantic meaning to the utterance. We also discuss the possibility of using this approach for semantic-based correction of an utterance. The experiments were performed on transcribed data as well as on an output from speech recognizer.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

<a href="/cs/project/TE01020197" target="_blank" >TE01020197: Centrum aplikované kybernetiky 3</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Text, Speech, and Dialogue, 17th International Conference, TSD 2014, Brno, Czech Republic, September 8-12, 2014. Proceedings

ISBN

978-3-319-10815-5

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

8

Strana od-do

563-570

Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

Brno, Czech Republic

Datum konání akce

8. 9. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—