Voice Activation Using Speaker Recognition for Controlling Humanoid Robot

Abstract

Voice activation and speaker recognition are needed in many applications today. Speaker recognition is the process of automatically recognizing who speaks based on the voice signal. The introduction of these speakers is generally required on systems that use security and privacy. One example of this paper application is for activation and security in controlling humanoid robots. Voice recording process using Kinect 2.0. The first step in the speech recognition process is feature extraction. In this paper use Mel Frequency Cepstrum Coefficient (MFCC) on characteristic extraction process and Dynamic Time Warping (DTW) used as feature matching technique. The test was performed by 5 different speakers, with 2 types of words (“aktifkan” means activate and “hello slim”), and test with different recording distance (0.5m, 2m, 4m). Robot activation using two different types of words has an average accuracy of 91.5%. At the next difficulty level for testing the recording distance accuracy decreased from 97.5% to 85% to 65%.