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Journal : Knowbase : International Journal of Knowledge in Database

End-to-End Text-to-Speech for Minangkabau Pariaman Dialect Using Variational Autoencoder with Adversarial Learning (VITS) Fakhrezi, Muhammad Dzaki; Yusra; Muhammad Fikry; Pizaini; Suwanto Sanjaya
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 1 (2025): June 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i1.9909

Abstract

Language serves as a medium of human communication to convey ideas, emotions, and information, both orally and in writing. Each language possesses vocabulary and grammar adapted to the local culture. One of the regional languages that enriches Indonesian as the national language is Minangkabau. This language has four main dialects, namely Tanah Datar, Lima Puluh Kota, Agam, and Pesisir. Within the Pesisir dialect, there are several variations, including the Padang Kota, Padang Luar Kota, Painan, Tapan, and Pariaman dialects. This study discusses the application of Text-to-Speech (TTS) technology to the Minangkabau language, specifically the Pariaman dialect, using the Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech (VITS) method. This dialect needs to be preserved to prevent extinction and supported through technological development that broadens its use. The VITS method was chosen because it is capable of producing natural and high-quality speech. The research stages include voice data collection and recording, VITS model training, and speech quality evaluation using the Mean Opinion Score (MOS). The final results show a score of 4.72 out of 5, indicating that the generated speech closely resembles the natural utterances of native speakers. This TTS technology is expected to support the preservation and development of the Minangkabau language in the Pariaman dialect, as well as enhance information accessibility for its speakers.
Co-Authors Abdussalam Al Masykur Adrian Maulana Afiana Nabilla Zulfa Ahmad Fauzan Ahmad Paisal Ahmad, Rizmah Zakiah Nur Al Fiqri, M. Faiz Alwis Nazir Alwis Nazir Alwis Nazir Alwiz Nazir Amalia Hanifah Artya Annisa Putri Aqilah, M Alfandri Arif Mudi Priyatno Ariq At-Thariq Putra Aulia Ramadhani Baehaqi Cut Lira Kabaatun Nisa Darmila Deny Ardianto Dodi Efendi efni humairah Eka Pandu Cynthia Elin Haerani Elvia Budianita Erni Rouza, Erni Ersad Alfarsy Absar, Ersad Alfarsy Fadhilah Syafria Fadhilla Syafria Fakhrezi, Muhammad Dzaki Febi Yanto Felian Nabila Fitri Insani Fitri Insani Fitri Insani (Scopus ID: 57190404820) Fitri, Dina Deswara Gusrifaris Yuda Alhafis Gusti, Siska Kurnia Hafez Almirza Hardiansyah, Muhammad Vio Harni, Yulia Hartini Hartini Iis Afrianty Iis Afrianty Ikhwanul Akhmad DLY Insani (Scopus ID: 57190404820), Fitri Irman Hermadi Isnan Mellian Ramadhan Israldi, Tino Iwan Iskandar Iwan Iskandar Jasril Jasril Jasril Jasril Jasril Jasril Karina Julita Kurnia Rahman, Fikri Kurniawan, Saifur Yusuf Lestari Handayani Lestari Handayani Lestari Handayani Lia Anggraini Lola Oktavia M. Fadil Martias Masaugi, Fathan Fanrita Maulana Junihardi Mazdavilaya, T Kaisyarendika Megawati Megawati Morina Lisa Pura Muhammad Affandes Muhammad Fikry Muhammad Irfan Syah Muhammad Irsyad Muhammad Irsyad Nabyl Alfahrez Ramadhan Amril Nazir, Alwis Nazruddin Safaat Nazruddin Safaat H Negara, Benny Sukma Novi Yanti Novriyanto Novriyanto Novriyanto Pangestu, Yoga Pizaini Pizaini Puspa Melani Almahmuda Putri Ayuni, Desy Radili, Adi Rahma Shinta Rahmad Abdillah Rahmad Abdillah Ramadhan, Muhammad Ilham Ramu Will Sandra Reski Mai Candra Reski Mai Candra Reski Mei Candra Riska Yuliana Saputra, Nugroho Wahyu Sarah Lasniari Sarah Lasniari Shahira, Fayza Sugandi, Hatami Karsa SURYA ADITYA GD Surya Agustian Syaputra, Muhammad Dwiky Ulfah Adzkia Vitriani, Yelfi Yani, Susmi Syahfrida Yelfi Vitriani Yeni Fariati Yusra Yusra, Yusra Yusril Hidayat