Recognizing word gesture in sign system for Indonesian language (SIBI) Sentences using DeepCNN and BiLSTM

Noer Fitria Putra Setyono, Erdefi Rakun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

SIBI is a sign language that is officially used in Indonesia. The use of SIBI is often found to be a problem because of the many gestures that have to be remembered. This study aims to recognize SIBI gestures by extracting hand and facial features which are then classified using Bidirectional Long ShortTerm Memory (BiLSTM). The feature extraction used in this research is Deep Convolutional Neural Network (DeepCNN) such as ResNet50 and MobileNetV2, where both models are used as a comparison. This study also compares the performance and computational time between the two models which is expected to be applied to smartphones later, where both models can now be implemented on smartphones. The results showed that the use of ResNet50-BiLSTM model have better performance than MobileNetV2-BiLSTM which is 99.89%. However, if it will be applied to mobile architecture, MobileNetV2-BiLSTM is superior because it has a faster computational time with a performance that is not significantly different when compared to ResNet50-BiLSTM.

Original languageEnglish
Title of host publication2019 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages199-204
Number of pages6
ISBN (Electronic)9781728152929
DOIs
Publication statusPublished - Oct 2019
Event11th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2019 - Bali, Indonesia
Duration: 12 Oct 201913 Oct 2019

Publication series

Name2019 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2019

Conference

Conference11th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2019
CountryIndonesia
CityBali
Period12/10/1913/10/19

Keywords

  • BiLSTM
  • DeepCNN
  • Feature Extraction
  • MobileNetV2
  • ResNet50
  • SIBI
  • Sign Language Recognition

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