N-gram language Models in JLASER Neural Network Speech Recognizer
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F10%3A00503932" target="_blank" >RIV/49777513:23520/10:00503932 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
N-gram language Models in JLASER Neural Network Speech Recognizer
Original language description
In our recent research we have discovered that neural networks can be more efficient in pseech reognition than the state of the art approach based on Gaussian mixtures. This statement is valid only for small corpora, however, many applications do not require a huge recognition vocabulary. In this article we describe our speech reognizer - called JLASER - based on neural networks. We also show the effect of n-gram language models applied to the JLASER recognizer.
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/2C06009" target="_blank" >2C06009: Complex knowledge base tools for natural language communication with the semantic web</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Applied Electronics
ISBN
978-80-7043-865-7
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
167-170
Publisher name
Západočeská univerzita
Place of publication
Plzeň
Event location
Plzeň
Event date
Sep 8, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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