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

Suhartono, Suhartono (2018) Speaker Recognition in Content-based Image Retrieval for a High Degree of Accuracy. Bulletin of Electrical Engineering and Informatics, 7 (3). pp. 350-358. ISSN 2302-9285

Text (full text)
3746.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Preview
Full text available at: http://journal.portalgaruda.org/index.php/EEI/arti...


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

Item Type: Journal Article
Keywords: Fuzzy Mamdani; Identification; Manhattan distance; Speaker recognition; Verification
Subjects: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision
Divisions: Faculty of Technology > Department of Informatics Engineering
Depositing User: Dr Suhartono M.Kom
Date Deposited: 04 Sep 2018 09:32


Downloads per month over past year

Origin of downloads

Actions (login required)

View Item View Item