INDIVIDUAL IDENTIFICATION SYSTEM DESIGN THROUGH VOICE USING LINEAR PREDICTIVE CODING METHOD AND K-NEAREST NEIGHBOR

Davita Nadia Fadhilah (Telecommunication Engineering, Electrical Engineering Faculty, Telkom University, Indonesia)
Rita Magdalena (Telecommunication Engineering, Electrical Engineering Faculty, Telkom University, Indonesia)
Sofia Sa’idah (Telecommunication Engineering, Electrical Engineering Faculty, Telkom University, Indonesia)

Jurnal Teknik Informatika (JUTIF)
Vol. 2 No. 2 (2021): JUTIF Volume 2, Number 2, December 2021

Humans have a variety of characteristics that are different from one another. Characteristics possessed by humans are genuine which can be used as a differentiator between one individual and another, one of which is sound. Voice recognition is called speech recognition. In this study, it was developed as an individual voice recognition system using a combination of the Linear Predictive Coding (LPC) method of feature extraction and K-Nearest Neighbor (K-NN) classification in the speech recognition process. Testing is done by testing changes in several parameters, namely the LPC order value, the number of frames, the K value, and different distance methods. The results of the parameter combination test showed a fairly good presentation of 73.56321839% with the combination parameter or LPC 8, the number of frames 480, the value of K 5, with the distance method used by Chebychev.