Word-Semantic Lattices for Spoken Language Understanding

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F15%3A43926626" target="_blank" >RIV/49777513:23520/15:43926626 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7178976&tag=1" target="_blank" >http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7178976&tag=1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICASSP.2015.7178976" target="_blank" >10.1109/ICASSP.2015.7178976</a>

Result language
angličtina
Original language name
Word-Semantic Lattices for Spoken Language Understanding
Original language description
The paper presents a method for converting word-based automatic speech recognition (ASR) lattices into word-semantic (W-SE) lattices that contain original words together with a partial semantic information – so-called semantic entities. Semantic entity detection algorithm generates semantic entities based on the expert-defined knowledge. The generated W-SE lattices have smaller vocabulary and consequently reduce the sparsity of the training data. The format of the W-SE lattices also naturally preserves the inherent uncertainty of the ASR output that can be exploited in subsequent dialog modules. The presented technique employs the framework of weighted finite state transducers which allows for efficient optimization of word-semantic lattices. We have evaluated the method in two different spoken language understanding tasks and obtained more than 10% reduction of concept error rate in comparison with using 1-best word hypothesis in both of those tasks.
Czech name
—
Czech description
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Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
ISBN
978-1-4673-6997-8
ISSN
1520-6149
e-ISSN
—
Number of pages
5
Pages from-to
5266-5270
Publisher name
IEEE
Place of publication
New York
Event location
Brisbane, Australia
Event date
Apr 19, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000427402905077

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