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International Journal of Speech Technology
Erschienen in: International Journal of Speech Technology 2/2015

01.06.2015

Nature-inspired feature subset selection application to arabic speaker recognition system

Erschienen in: International Journal of Speech Technology | Ausgabe 2/2015

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Abstract

Feature selection is an important task which can affect the performance of pattern classification and recognition system. This study uses two nature-inspired algorithms, namely genetic algorithms and particle swarm optimization, for this problem. The algorithms adopt classifier performance and the number of the selected features as heuristic information, and select the optimal feature subset in terms of feature set size and classification performance. From experimental results, the major contribution of this work are: the reduction of vector feature size without loosing performance which is crucial for real time application and low-resources devices as well as the time needed to find the optimal subset features compared to exhaustive search or other conventional methods (less than 50 iterations instead of billions of iterations to test all possible configurations).
Vorheriger Artikel Modeling user response timings in spoken dialog systems
Nächster Artikel Source and system features for phone recognition

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Literatur
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Metadaten
Titel
Nature-inspired feature subset selection application to arabic speaker recognition system
Publikationsdatum
01.06.2015
Erschienen in
International Journal of Speech Technology / Ausgabe 2/2015
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-014-9264-2

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