Language Identification Using Wavelet Transform and Artificial Neural Network

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F10%3A86077714" target="_blank" >RIV/61989100:27240/10:86077714 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Language Identification Using Wavelet Transform and Artificial Neural Network
Original language description
In traditional language identification methods, it is not so easy for search engines to find relevant language database of a given query. Therefore, there is a need to identify the relevant user's natural language query of unknown document database in abetter way by automatic language identification. This novel approach presents an automatic method for classification of English and Arabic language identification. The classifier used is a three-layered feed-forward artificial neural network and the feature vector is formed by calculating the wavelet coefficients. Three wavelet decomposition functions (filters), namely Haar, Bior 2.2 and Bior 3.1 have been used to extract the feature vector set and their performance has been compared.
Czech name
—
Czech description
—

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2010 International Conference on Computational Aspects of Social Networks
ISBN
978-0-7695-4202-7
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
—
Publisher name
IEEE Computer Society
Place of publication
Los Alamitos, California
Event location
Taiyuan, China
Event date
Sep 26, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)