Speaker Recognition in Content-based Image Retrieval for a High Degree of Accuracy

Abstract

The purpose of this research is to measure the speaker recognition accuracy in Content-Based Image Retrieval. To support research in speaker recognition accuracy, we use two approaches for recognition system: identification and verification, an identification using fuzzy Mamdani, a verification using Manhattan distance. The test results in this research. The best of distance mean is size 32x32. The best of the verification for distance rate is 965, and the speaker recognition system has a standard error of 5% and the system accuracy is 95%. From these results, we find that there is an increase in accuracy of almost 2.5%. This is due to a combination of two approaches so the system can add to the accuracy of speaker recognition.