Implementation of Sibi Sign Language Realtime Detection Program (Case Studi At Sekolah Luar Biasa Negeri 1 Tabanan)
DOI:
10.47709/cnahpc.v6i3.4405Keywords:
Gesture, Hand Sign, SIBI, Ultralytics, YoloV8Dimension Badge Record
Abstract
Indonesian deaf people utilize SIBI to communicate using spoken words, gestures, facial expressions, and body language. SIBI, certified for Special Schools (SLB), helps deaf pupils communicate. This project implements SIBI (Indonesian Sign Language System) a real-time detection algorithm at Sekolah Luar Biasa Negeri 1 Tabanan using image processing and YoloV8 ultralytics deep learning. The program trains a sign language gesture detection model on Google Colab's GPU. The SIBI sign language images were used to train a YoloV8 object detection model. The camera captures movements, which the YoloV8 algorithm trained on SIBI gesture data processes. It can recognize gestures in real time and generate text to non-sign language users. The dataset has 107 class vocabulary and 7 class affix prefixes for complete gesture recognition. Shirt color, room brightness, and webcam quality affect detection rates. Optimal detection accuracy is 87.74% and subpar 58.02%. Despite these limitations, the strategy helps deaf students communicate more effectively with non-sign language speakers. This program improves inclusivity and communication in schools, making learning easier for hearing-impaired pupils. This work provides a reliable and quick sign language identification system to help deaf educators and caregivers with daily interactions and education.
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References
Akhand, M. A. H., Roy, S., Siddique, N., Kamal, M. A. S., & Shimamura, T. (2021). Facial emotion recognition using transfer learning in the deep CNN. Electronics (Switzerland), 10(9). https://doi.org/10.3390/electronics10091036
Alharthi, N. M., & Alzahrani, S. M. (2023). Vision Transformers and Transfer Learning Approaches for Arabic Sign Language Recognition. Applied Sciences, 13(21), 11625. https://doi.org/10.3390/app132111625
Bhavana, D., Kishore Kumar, K., Chandra, M. B., Sai Krishna Bhargav, P. V., Joy Sanjana, D., & Mohan Gopi, G. (2021). Hand sign recognition using cnn. International Journal of Performability Engineering, 17(3), 314–321. https://doi.org/10.23940/ijpe.21.03.p7.314321
Farkaš, L. (2023). OBJECT TRACKING AND DETECTION WITH YOLOV8 AND STRONGSORT ALGORITHMS CAPTURED BY DRONE.
Hayyu Gustsa, A., & Setyo Permadi, G. (2023). Sistem Deteksi Bahasa Isyarat Secara Realtime Dengan Tensorflow Object Detection dan Python Menggunakan Metode Convolutional Neural Network. https://ejournal.unhasy.ac.id/index.php/inovate/article/view/4116
Istiqomah, F., Prasetyoningsih, L. S. A., Ambarwati, A., & Wahyuni, S. (2023). Positive Effects of SIBI Alphabet Cards on Increasing Vocabulary Acquisition in Children with Special Needs Deaf. AL-ISHLAH: Jurnal Pendidikan, 15(3), 3287–3294. https://doi.org/10.35445/alishlah.v15i3.2594
Lian, F., Gunardi, W., Made, G., Desnanjaya, N., Sudiarsa, W., Komputer, S., & Indonesia, S. (2022). Sistem Pendeteksian Masker dan Hand sanitizer Otomatis Berbasis Raspberry Pi. Journal of Practical Computer Science, 1(2), 12–24.
Luján-García, J. E., Yáñez-Márquez, C., Villuendas-Rey, Y., & Camacho-Nieto, O. (2020). A transfer learning method for pneumonia classification and visualization. Applied Sciences (Switzerland), 10(8). https://doi.org/10.3390/APP10082908
Narlan, R., Puji Widiyanto, E., & Sumatera Selatan, B. (2023). AUTOMATED PAVEMENT DEFECT DETECTION USING YOLOv8 OBJECT DETECTION ALGORITHM. Prosiding KRTJ HPJI, 16(1), 1–13.
Salsabila, A. (2022). ARKANA Jurnal Komunikasi dan Media POLA KOMUNIKASI GURU TERHADAP SISWA TUNARUNGU (Studi Kasus Siswa Sekolah Dasar Di SLB-B Don Bosco Wonosobo).
Shirbhate, R. S., Shinde, V. D., Metkari, S. A., Borkar, P. U., Khandge, M. A., -Wagholi, B., & ---------------------------------------------------------------------, P. (2020). Sign language Recognition Using Machine Learning Algorithm. International Research Journal of Engineering and Technology. www.irjet.net
Sri Nugraheni, A., Pratiwi Husain, A., & Unayah, H. (2021). OPTIMALISASI PENGGUNAAN BAHASA ISYARAT DENGAN SIBI DAN BISINDO PADA MAHASISWA DIFABEL TUNARUNGU DI PRODI PGMI UIN SUNAN KALIJAGA.
Sudiarsa, I. wayan, Sugiartawan, P., Sudipa, I. G. I., Maharianingsih, N. M., & Putra, I. K. A. (2023). Sistem Pengering Daun Kelor Berbasis Internet of Things dan Artificial Intteligence. IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), 13(2), 183. https://doi.org/10.22146/ijeis.89823
Tadic, V., Odry, A., Vizvari, Z., Kiraly, Z., Felde, I., & Odry, P. (2024). Electric Vehicle Charging Socket Detection using YOLOv8s Model. In Acta Polytechnica Hungarica (Vol. 21, Issue 10).
Tang, M. (2024). A real-time traffic sign detection in intelligent transportation system using YOLOv8-based deep learning approach. Signal, Image and Video Processing. https://doi.org/10.1007/s11760-024-03300-3
Wirta, I. W., Supriadi, I. B. P., & Maharani, I. A. K. (2021). Communication Behaviour of Deaf Children in SLB Negeri 1 Tabanan: Ethnographic Communication Perspective. IJDS: Indonesian Journal of Disability Studies, 8(01), 295–303. https://doi.org/10.21776/ub.ijds.2021.008.01.18
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