A study of different weighting schemes for spoken language understanding based on convolutional neural networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F16%3A43929967" target="_blank" >RIV/49777513:23520/16:43929967 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7472842" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7472842</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICASSP.2016.7472842" target="_blank" >10.1109/ICASSP.2016.7472842</a>
Alternative languages
Result language
angličtina
Original language name
A study of different weighting schemes for spoken language understanding based on convolutional neural networks
Original language description
This paper describes the development of a stateless spoken spoken language understanding (SLU) module based on artificial neural networks that is able to deal with the uncertainty of the automatic speech recognition (ASR) output. The work builds upon the concept of weighted neurons introduced by the authors previously and presents a generalized weighting term for such a neuron. The effect of different forms and parameter estimation methods of the weighting term is experimentally evaluated on the multi-task training corpus, created by merging two different semantically annotated corpora. The robustness of the best performing weighting schemes is then demonstrated by experiments involving hybrid word-semantic (WSE) lattices and also limited data scenario.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20205 - Automation and control systems
Result continuities
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)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2016 IEEE International Conference on Acoustics, Speech, and Signal Processing Proceedings
ISBN
978-1-4799-9988-0
ISSN
2379-190X
e-ISSN
—
Number of pages
5
Pages from-to
6065-6069
Publisher name
IEEE Signal Processing Society
Place of publication
New York
Event location
Shanghai, China
Event date
May 20, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000388373406044