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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Speech-to-Text Conversion in Indonesian Language Using a Deep Bidirectional Long Short-Term Memory Algorithm
Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120327
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 3, 2021.
Abstract: Nowadays, speech is used also for communication between humans and computers, which requires conversion from speech to text. Nevertheless, few studies have been performed on speech-to-text conversion in Indonesian language, and most studies on speech-to-text conversion were limited to the conversion of speech datasets with incomplete sentences. In this study, speech-to-text conversion of complete sentences in Indonesian language is performed using the deep bidirectional long short-term memory (LSTM) algorithm. Spectrograms and Mel frequency cepstral coefficients (MFCCs) were utilized as features of a total of 5000 speech data spoken by ten subjects (five males and five females). The results showed that the deep bidirectional LSTM algorithm successfully converted speech to text in Indonesian. The accuracy achieved by the MFCC features was higher than that achieved with the spectrograms; the MFCC obtained the best accuracy with a word error rate value of 0.2745% while the spectrograms were 2.0784%. Thus, MFCCs are more suitable than spectrograms as feature for speech-to-text conversion in Indonesian. The results of this study will help in the implementation of communication tools in Indonesian and other languages.
Keywords: Speech-to-text; Deep Bidirectional Long Short-Term Memory (LSTM); spectrogram; Mel frequency cepstral coefficients (MFCC); word error rate
Suci Dwijayanti, Muhammad Abid Tami and Bhakti Yudho Suprapto, “Speech-to-Text Conversion in Indonesian Language Using a Deep Bidirectional Long Short-Term Memory Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 12(3), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120327
@article{Dwijayanti2021,
title = {Speech-to-Text Conversion in Indonesian Language Using a Deep Bidirectional Long Short-Term Memory Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120327},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120327},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {3},
author = {Suci Dwijayanti and Muhammad Abid Tami and Bhakti Yudho Suprapto}
}
