Identifikasi Pola Suara Pada Bahasa Jawa Meggunakan Mel Frequency Cepstral Coefficients (MFCC)
Abstract
Voice Recognition is a process of developing systems used between computer and human. The purpose of this study is to find out the sound pattern of a person based on the spoken Javanese language. This study used the Mel Frequency Cepstral Coefficients (MFCC) method to solve the problem of feature extraction from human voices. Tests were carried out on 4 users consisting of 2 women and 2 men, each saying 1 word "KUTHO", the word pronounced 5 times. The results of the testing are to get a sound pattern from the characteristics of 1 person with another person so that research using the MFCC method can produce different sound patterns
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I. Agustina, F. Fauziah, and A. Gunaryati, “Biometrik Pola Suara Dengan Jaringan Saraf Tiruan,†J. Tek. Inform., vol. 9, no. 2, pp. 140–147, 2018.
I. N. K. Wardana and I. G. Harsemadi, “Identifikasi Biometrik Intonasi Suara untuk Sistem Keamanan Berbasis Mikrokomputer,†J. Sist. Dan Inform., vol. 9, no. 1, pp. 29–39, 2014.
M. Pendidikan, D. A. N. Kebudayaan, and R. Indonesia, “MENTERI PENDIKAN PERATURAN MENTERI PENDIDIKAN DAN KEBUDAYAAN REPUBLIK INDONESIA NOMOR 26 TAHUN 2017,†2017.
J. Adler, M. Azhar, and S. Supatmi, “Identifikasi Suara dengan MATLAB sebagai Aplikasi Jaringan Syaraf Tiruan Speech Recognition in MATLAB as Artificial Neural Network Application,†vol. 1, no. 1, pp. 16–23, 2013.
R. Aisuwarya, K. I. Putri, and M. H. Hersyah, “IMPLEMENTASI SPEECH RECOGNITION SEBAGAI SISTEM KONTROL PADA SMART HOME BERBASIS MIKROKONTROLER MENGGUNAKAN METODE HIDDEN MARKOV MODEL ( HMM ),†2017.
E. Widiyanto, S. N. Endah, and S. Adhy, “APLIKASI SPEECH TO TEXT BERBAHASA INDONESIA MENGGUNAKAN MEL FREQUENCY CEPSTRAL COEFFICIENTS DAN HIDDEN MARKOV MODEL ( HMM ),†pp. 39–44, 2014.
R. Bogdan et al., “Kendali Suara Berbahasa Indonesia Untuk Automasi Rumah Tinggal,†vol. 11, no. 1, pp. 1–6, 2018.
R. Firmansyah, E. C. Djamal, R. Yuniarti, J. Informatika, and F. Sains, “Identifikasi Nada Dari Sinyal Suara Alat Musik Instrumen Menggunakan Metode Mel Frequency Cepstrum Coefficients dan Hidden Markov Model,†pp. 7–12, 2018.
J. T. Elektro, U. Brawijaya, and A. Mustofa, “Sistem Pengenalan Penutur dengan Metode Mel-frequency Wrapping,†vol. 7, no. 2, pp. 88–96, 2007.
A. R. Darma Putra, “Verifikasi Biometrika Suara Menggunakan Metode MFCC Dan DTW Darma,†LONTAR Komput. VOL. 2 NO.1 JUNI 2011, vol. 2, no. 1, pp. 8–21, 2011.
S. Helmiyah, A. Fadlil, A. Yudhana, M. T. Informatika, and U. A. Dahlan, “Pengenalan Pola Emosi Manusia Berdasarkan Ucapan Menggunakan Ekstraksi Fitur Mel-Frequency Cepstral Coefficients ( MFCC ) Speech Based Emotion Pattern Recognition Using Mel- Frequency Cepstral Coefficients ( MFCC ) Feature Extraction,†vol. 4, no. 2, pp. 372–381, 2018.
DOI: https://doi.org/10.30865/mib.v4i1.1793
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