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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics
Suhartono Suhartono
UIN Maulana Malik Ibrahim
Computer Science & IT Electrical & Electronics Engineering Engineering

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Speaker Recognition in Content-based Image Retrieval for a High Degree of Accuracy Suhartono Suhartono; Fresy Nugroho; Muhammad Faisal; Muhammad Ainul Yaqin; Suyanta Suyanta
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (728.047 KB) | DOI: 10.11591/eei.v7i3.957

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.
Speaker Recognition in Content-based Image Retrieval for a High Degree of Accuracy Suhartono Suhartono; Fresy Nugroho; Muhammad Faisal; Muhammad Ainul Yaqin; Suyanta Suyanta
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (728.047 KB) | DOI: 10.11591/eei.v7i3.957

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.
Speaker Recognition in Content-based Image Retrieval for a High Degree of Accuracy Suhartono Suhartono; Fresy Nugroho; Muhammad Faisal; Muhammad Ainul Yaqin; Suyanta Suyanta
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (728.047 KB) | DOI: 10.11591/eei.v7i3.957

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.
Co-Authors Fresy Nugroho Muhammad Ainul Yaqin Muhammad Faisal Suyanta Suyanta