Aplikasi Penerjemah Kegiatan Seminar Menjadi Video Bahasa Isyarat BISINDO Dengan Speech To Text

Marcel Slamet Sugianto, Liliana Liliana, Anita Nathania Purbowo

Abstract


Information at this time is very much needed to increase our knowledge. However, this delivery can be hindered by several conditions such as the inability to hear the deaf community. Based on data from the Data and Information Center of the Ministry of Health of the Republic of Indonesia in 2019, 7.09% of the Indonesian population is deaf. In addition, the delivery of information at the seminar can be hindered by noise and participants sitting far from the speaker will have difficulty hearing the speaker's voice. In this study, we will use Speech-To-Text on the Android application which aims to help translate information in the form of voice delivered as at a seminar into text and will be converted into BISINDO sign language video. The results of testing the use of the Speech-To-Text feature in the application that has been made show that it is able to accommodate approximately 100 words in 1 minute at a time when the speaker speaks without any pause. The Speech-To-Text feature used takes approximately 2 seconds to translate the received voice and the time lag required by the speaker device to the participant's device takes approximately 3-5 seconds after using 5 different internet speeds. For the accuracy of the Speech-To-Text feature that was tested using 3 narrations read by 4 different people, the accuracy of the Speech-To-Text feature has an accuracy of above 80% in general, although there is an accuracy that is below 80% due to the ambiguity of the pronunciation.

Keywords


Kotlin; Hand Sign; BISINDO; Mobile Application; Seminar; Speech-To-Text.

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References


Gumelar, G., Hafiar, H., & Subekti, P. (2018). KONSTRUKSI

MAKNA BISINDO SEBAGAI BUDAYA TULI BAGI

ANGGOTA GERKATIN. Informasi, 48(1), 65-78. DOI:

21831/informasi.v48i1.17727

Khan, R. Z., & Ibraheem, N. A. (2012). Survey on Gesture

Recognition for Hand Image Postures. Computer and

Information Science, 5(3). DOI: 10.5539/cis.v5n3p110

Khilari, P., & Bhope, V. P. (2015). A REVIEW ON SPEECH

TO TEXT CONVERSION METHODS. International Journal

of Advanced Research in Computer Engineering &

Technology (IJARCET), 4(7). ISSN: 2278 –1323

Kothadiya, D., Pise, N., & Bedekar, M. (2020). Different

Methods Review for Speech to Text and Text to Speech

Conversion. International Journal of Computer Applications,

, 8887. DOI: 10.1007/s11042-020-10073-7

Mitra, S., & Acharya, T. (2007). Gesture Recognition: A

Survey. IEEE Transactions on Systems, Man and Cybernetics,

Part c (Applications and Reviews), 37(3), 311–324. DOI:

1109/TSMCC.2007.893280

Pavlovic, V. I., Sharma, R., & Huang, T. S. (1997). Visual

interpretation of hand gestures for human-computer

interaction: a review. IEEE Transactions on Pattern Analysis

and Machine Intelligence, 19(7), 677–695. DOI:

1109/34.598226

Singh, A. P., Nath, R., & Kumar, S. (2018, November). A

survey: Speech recognition approaches and techniques. In

5th IEEE Uttar Pradesh Section International

Conference on Electrical, Electronics and Computer

Engineering (UPCON) (pp. 1-4). IEEE. DOI:

1109/UPCON.2018.8596954

Trivedi, A., Pant, N., Shah, P., Sonik, S., & Agrawal, S.

(2018). Speech to text and text to speech recognition systemsAreview. IOSR J. Comput. Eng, 20(2), 36-43. DOI:

9790/0661-2002013643

Vadwala, A. Y., Suthar, K. A., Karmakar, Y. A., & Thakkar,

N. (2017). Survey paper on Different Speech Recognition

Algorithm: Challenges and Techniques SAMVAD-Speak Ask

Manage Via Android Device View project Survey paper on

Different Speech Recognition Algorithm: Challenges and

Techniques. International Journal of Computer Applications,

(1). DOI: 10.1109/TSMCC.2007.893280

Zulpicha, E. (2017). Konflik Kebijakan Penggunaan Sistem

Bahasa Isyarat Indonesia di Lingkungan Pendidikan Formal.

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