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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmiah Informatika Komputer Prosiding KOMMIT Jurnal Ilmiah KOMPUTASI Jurnal Ilmiah Matrik STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Engineering, Mathematics and Computer Science Journal (EMACS) prosiding seminar nasional International Journal Science and Technology (IJST) Jurnal Teknik dan Science (JTS) Jurnal Ilmiah Multidisiplin (JUKIM) Jurnal Bina Komputer Enrichment: Journal of Multidisciplinary Research and Development
Nuryuliani Nuryuliani
Universitas Gunadarma
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Social Sciences Other

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Journal : Engineering, Mathematics and Computer Science Journal (EMACS)

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Implementation of Optical Character Recognition and Voice Recognition of House of Words (How) Dictionary Application on Android Platform Hutami Septiana Raswaty; Nuryuliani Nuryuliani
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 3 No. 3 (2021): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v3i3.7418

Abstract

People with different languages need to be assisted by translator to establish the communication between them. The technology development which exists to fulfill communication needs is digital dictionary as translator tool. The capability of digital dictionary to translate the languages yet has a weakness in putting the input. Through this research, Optical Character Recognition using Tesseract library and Voice Recognition technologies using Google Speech-To-Text are used to replace the previous input system. Based on the implementation and testing, the OCR and Voice Recognition have been successfully recognizing the text and voice input with the amount of similarity of 92,72% for OCR and 95,46% for Voice Recognition. The result of the implementation is expected to help a group of people with different language to communicate easily.
Co-Authors Dwi Handayani Elfitrin Syahrul Erfan Erfan Faisal Akbar Hakim, Arif Rachman Haq, Fesa Asy Syifa Nurul Hutami Septiana Raswaty Kristian, Alex Lulu C Munggaran Lulu C. Munggaran Lulu Chaerani M. Muhammad Rafi Pradana Muhammad Sesio Dhia Ramadhan Nur Azmi Ratna Setyawidati Nur Azmi Ratna Setyawidati Rachman, Aditya Fadhli Suryarini Widodo Yusliana Iskantika Yusliana Iskantika Zelin Gaa Ngilo