Hierachical Arabic Phoneme Recognition using MFCC Analysis
In this paper, a hierarchical Arabic phoneme recognition system is proposed in which Mel FrequencyCepstrum 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 ofpho...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
College of Engineering, University of Basrah
2007-01-01
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| Series: | Iraqi Journal for Electrical and Electronic Engineering |
| Subjects: | |
| Online Access: | http://ijeee.org/volums/volume3/IJEEE3PDF/39.pdf |
| Summary: | In this paper, a hierarchical Arabic phoneme recognition system is proposed in which Mel FrequencyCepstrum 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 ofphonemes. 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. |
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| ISSN: | 1814-5892 2078-6069 |