Classification of emphatic consonants and their counterparts in Modern Standard Arabic using neural networks | IEEE Conference Publication | IEEE Xplore

Classification of emphatic consonants and their counterparts in Modern Standard Arabic using neural networks


Abstract:

This paper presents the work of acoustic analysis related to Modern Standard Arabic (MSA). The problem of classifying the consonant counterparts in MSA is tackled here. T...Show More

Abstract:

This paper presents the work of acoustic analysis related to Modern Standard Arabic (MSA). The problem of classifying the consonant counterparts in MSA is tackled here. The study considers four phonemes: /dς, ∂ς/ and their non-emphatic counterparts /d, ∂ς/ respectively. An accurate automatic classification for those phonemes is to be achieved. Artificial neural networks (ANNs) are used for that purpose. The multilayer perceptron (MLP) is applied to the features extracted from the speech signals. The speech utterances used in this study are from KAPD database. Classification accuracy of 83.9% was achieved.
Date of Conference: 15-17 December 2014
Date Added to IEEE Xplore: 26 October 2015
ISBN Information:
Print ISSN: 2162-7843
Conference Location: Noida, India

References

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