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Speech Recognition Using Combined Fuzzy and Ant Colony algorithm

Jalili, FooadJafari Barani, Milad
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 Oktober 2016
DOI10.11591/ijece.v6i5.pp2205-2210

Abstrak

In recent years various methods has been proposed for speech recognition and removing noise from the speech signal became an important issue. In this paper a fuzzy system has been proposed for speech recognition that can obtain accurate results using classification of speech signals with “Ant Colony” algorithm.  First, speech samples are given to the fuzzy system to obtain a pattern for every set of signals that can be helpful for dimensionality reduction, easier checking of outcome and better recognition of signals.  Then, the “ACO” algorithm is used to cluster these signals and determine a cluster for each input signal. Also, with this method we will be able to recognize noise and consider it in a separate cluster and remove it from the input signal. Results show that the accuracy for speech detection and noise removal is desirable.

Kata Kunci

Computer and InformaticsSpeech recognitionFuzzy logicAnt ColonyNoise removalClustering

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Speech Recognition Using Combined Fuzzy and Ant Colony algorithm | International Journal of Electrical and Computer Engineering (IJECE) | Publiora