Abstract
The deaf-mutes population is constantly feeling helpless when others do not understand them and vice versa. To fill this gap, this study implements a CNN-based neural network, Convolutional Based Attention Module (CBAM), to recognise Malaysian Sign Language (MSL) in videos recognition. This study has created 2071 videos for 19 dynamic signs. Two different experiments were conducted for dynamic signs, using CBAM-3DResNet implementing ‘Within Blocks’ and ‘Before Classifier’ methods. Various metrics such as the accuracy, loss, precision, recall, F1-score, confusion matrix, and training time were recorded to evaluate the models’ efficiency. Results showed that CBAM-ResNet models had good performances in videos recognition tasks, with recognition rates of over 90% with little variations. CBAM-ResNet ‘Before Classifier’ is more efficient than ‘Within Blocks’ models of CBAM-ResNet. All experiment results indicated the CBAM-ResNet ‘Before Classifier’ efficiency in recognising Malaysian Sign Language and its worth of future research.
Highlights
Malaysia Sign Language or Bahasa Isyarat Malaysia in Malay was founded in 1998 when the Malaysia Federation of the Deaf (MFD) was established [1]
This study introduced the Convolutional Based Attention Module (CBAM)-Residual Network (ResNet) neural network to resolve the problems such as accuracy and applicability in the previous Malaysian Sign Language (MSL) recognition technology
This section will compare the results of CBAM-3DResNet of both ‘Within Blocks’ and ‘Before Classifier’ models
Summary
Malaysia Sign Language or Bahasa Isyarat Malaysia in Malay was founded in 1998 when the Malaysia Federation of the Deaf (MFD) was established [1]. It is the primary sign language in Malaysia. It is used for daily communication for the deaf-mute community, including deaf people, people with hearing impairments, and physically unable to speak. The American Sign Language (ASL) has a significant influence on MSL. There are a few similarities between the MSL and Indonesian Sign language, both are perceived as different. The foundation of Indonesian Sign language was based on MSL.
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