Abstract
Conference Title: 2014 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) Conference Start Date: 2014, Dec. 15 Conference End Date: 2014, Dec. 17 Conference Location: Noida, India 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: (ProQuest: Formulae and/or non US-ASCII text omitted) and their non-emphatic counterparts /d, ð/ 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.