Artificial Intelligence

   

Lie Detection System with Voice Using Bidirectional Associative Memory Algorithm

Authors: Bustami; Fadlisyah; Nurdania Delemunte

Lie detection through voice can be detected using the algorithm bidirectional associative memory. This system is a branch of sound processing that can be used to identify the type of sound lies use some verbs like go, roads and move. This study uses an algorithm bidirectional associative memory for the process and the introduction of lie detection training through the sound use of bidirectional associative memory. The system was tested by simulating the training data and test data to generate a percentage of voice recognition and classification of these lies. Experiments performed with several changes in parameter values to obtain the best percentage of recognition and classification. The highest level of recognition contained in the verb "go" with up to 90%. Results of this research is a sound that indicated not indicated lies and deceit in the form of values are classified according to the type of sound that is known from the results of calculations of energy use bidirectional associative memory.

Comments: 07 Pages. Figures :04 Tables : 03, IJCAT.org, Volume 2, Issue 8, August 2015

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[v1] 2015-09-18 04:00:41

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