Convert Gestures of Arabic Words into Voice

Ali, S. K., Al-Sherbaz, Ali ORCID: 0000-0002-0995-1262 and Aydam, Z. M. (2020) Convert Gestures of Arabic Words into Voice. Journal of Physics: Conference Series, 1591. art 012023.

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Abstract

Gestures are one of the best ways of communication between dumbs and other people using the expression of signs language. In this paper, we suggest an algorithm for recognizing hand gestures of Arabic words ()اتمنى لك حیاة سعیدة-اقتباس to by using dumb (through signs) and convert the sings into voice corresponding to sings words. The proposed algorithm for Convert Gestures of Arabic Words into Voice , record video of gesture ( of the dumb person ) then convert the video into frames (images), preprocessing for the resulted image must done by remove the noise, resize the images and increase the contrast, then calculate the distance to clustering the words by using (C4.5 , k-mean , k- medoid and artificial neural network), calculate the distance ( or features) by using Euclidean distance and slope where ,there are eighteen features (eight features from Euclidean distance, eight features from slop, Area, and perimeter). The results in the training stage were (C4.5 gave 100%, k-mean gave 95.2% k-medoid gave 91.9% and ANN gave 91.27%). While in the testing stage we used three classifiers (Euclidian Distance, Modify of the Standardize Euclidian Distance and Correlation) and the results show that (Euclidian Distance gave 94.4%,Modify of the Standardize Euclidian Distance gave 100% and Correlation gave 94.4% ) We create our database (three videos with 250 frames) for training and one video for testing.

Item Type: Article
Article Type: Article
Uncontrolled Keywords: Gestures; Feature Extraction; C4.5; K-Mean; K-Medoid and ANN
Subjects: P Language and Literature > PB Modern European Languages
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Schools and Research Institutes > School of Computing and Engineering > Technical & Applied Computing
Research Priority Areas: Applied Business & Technology
Depositing User: Kate Greenaway
Date Deposited: 11 Feb 2021 12:56
Last Modified: 01 Aug 2021 22:32
URI: https://eprints.glos.ac.uk/id/eprint/9353

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