Open AccessFinite State Automata Approach for Text to Speech Translation System in Indonesian-Madurese Language
Author(s) -
Fika Hastarita Rachman,
Qudsiyah,
Firdaus Solihin
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1569/2/022091
Subject(s) - indonesian , intonation (linguistics) , pronunciation , computer science , linguistics , syllable , language structure , state (computer science) , natural language processing , speech recognition , algorithm , philosophy
Madurese language is one of the regional languages in Indonesia. This laguage used by the Madurese people. Preservation of Madurese language now is minimal. Many migrants come from outside Madura, so communication between the surrounding communities in the Madura region often uses the national language, Indonesian. The use of Madurese as a language of communication began to decrease. This research is an effort to preserve Madurese language by utilizing the translator system technology. Madurese language is a regional language that is difficult to learn, because there are many differences found between writing and pronunciation. To overcome this problem this reasearch develop text to speech module in the Indonesian-Madurase language translation system. There are 3 versions of Madurese language level: Enja’-iyyeh, engghi-enten, and enggi-bunten. The conversion of text into sound is used with the help of syllable recording data created by the author. The process of chopping words into syllables is done using the two-level Finite State Automata (FSA) method. The output of the first level FSA becomes input for the second level. The application of FSA in Text to Speech applications is effectively used with accuracy value of 90%. The resulting sound output is in accordance with the results of syllables, but the pronunciation of some translated sentences does not have the correct intonation. The accuracy results of the intonation pattern in pronunciation of the system is 85%.