Semantic Entity Detection From Multiple ASR Hypotheses Within The WFST Framework
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F13%3A43920759" target="_blank" >RIV/49777513:23520/13:43920759 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ASRU.2013.6707710" target="_blank" >http://dx.doi.org/10.1109/ASRU.2013.6707710</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ASRU.2013.6707710" target="_blank" >10.1109/ASRU.2013.6707710</a>
Alternative languages
Result language
angličtina
Original language name
Semantic Entity Detection From Multiple ASR Hypotheses Within The WFST Framework
Original language description
The paper presents a novel approach to named entity detection from ASR lattices. Since the described method not only detects the named entities but also assigns a detailed semantic interpretation to them, we call our approach the semantic entity detection. All the algorithms are designed to use automata operations defined within the framework of weighted finite state transducers (WFST) the ASR lattices are nowadays frequently represented as weighted acceptors. The expert knowledge about the semantics ofthe task at hand can be first expressed in the form of a context free grammar and then converted to the FST form. We use a WFST optimization to obtain compact representation of the ASR lattice. The WFST framework also allows to use the word confusion networks as another representation of multiple ASR hypotheses. That way we can use the full power of composition and optimization operations implemented in the OpenFST toolkit for our semantic entity detection algorithm. The devised method
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/TE01020197" target="_blank" >TE01020197: Centre for Applied Cybernetics 3</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IEEE 2013 Workshop on Automatic Speech Recognition and Understanding
ISBN
978-1-4799-2756-2
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
84-89
Publisher name
IEEE Signal Processing Society
Place of publication
Piscataway
Event location
Olomouc
Event date
Dec 8, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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