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HIERARCHICAL ARABIC PHONEME RECOGNITION USING MFCC ANALYSIS | ||
| Iraqi Journal for Electrical And Electronic Engineering | ||
| Article 1, Volume 3, Issue 1, 2007, Pages 97-106 PDF (0 K) | ||
| DOI: 10.33762/eeej.2007.55285 | ||
| Authors | ||
| ABDULADHEM A; INTESSAR T. HWAIDY | ||
| Abstract | ||
| In this paper, a hierarchical Arabic phoneme recognition system is proposed in which Mel Frequency Cepstrum Coefficients (MFCC) features is used to train the hierarchical neural networks architecture. Here, separate neural networks (subnetworks) are to be recursively trained to recognize subsets of phonemes. The overall recognition process is a combination of the outputs of these subnetworks. Experiments that explore the performance of the proposed hierarchical system in comparison to nonhierarchical (flat) baseline systems are also presented in this paper. | ||
| Keywords | ||
| Speech Recognition; phoneme recognition; hierarchical systems; Mel cepstrum; neural networks | ||
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