Suprapto, Bhakti Yudho (2018) Similarity: Identification of RegionalDialectsUsingMel Frequency Cepstral Coefficients (MFCCs) andNeural Network. 2018 International Seminar on Application for Technology of Information and Communication, International Seminar on Application for Technology of Information and Communication.
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Abstract
Dialects may affect the voice recognition because they have an influence on the intonation and the pronunciation of a syllable. Every dialect shows the characteristic of a particular tribe and region. This paper addresses to develop a speech recognition system using Mel Frequency Cepstral Coefficients which are fed to a neural network based on backpropagation algorithm to recognize some particular dialects. The regional dialects used in this paper are Indonesian dialects, namely, Bataknese, Minang, and Javanese. The experiments are conducted to recognize the dialects from training and testing data. The testing data used in the experiments are from different people who have never been trained before so that it is expected that the recognition results will be more valid. The accuracy rate is used to evaluate the performance of the system. The accuracy of dialects recognition for Bataknese, Javanese and Minang are less than 20%, 50% - 80% and 70% - 90%, respectively. This method has succeeded in identifying the regional dialects and the most precise identification is on Minang and Javanese dialects.
| Item Type: | Other |
|---|---|
| Subjects: | #3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker |
| Divisions: | 03-Faculty of Engineering > 20201-Electrical Engineering (S1) |
| Depositing User: | Mr. Bhakti Suprapto |
| Date Deposited: | 18 Apr 2023 09:06 |
| Last Modified: | 18 Apr 2023 09:06 |
| URI: | http://repository.unsri.ac.id/id/eprint/94715 |
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