부산대학교 도서관

Sign language plays a critical role in facilitating communication among individuals with hearing or speaking disabilities. Until September 2021, signers from Kerala had to rely on Indian Sign Language (ISL), American Sign Language (ASL), or other regional sign languages to communicate. The introduction of Malayalam Sign Language (MSL) by National Institute of Speech Hearing, Thiruvananthapuram in September 2021 was a significant step towards addressing this issue. This paper presents a character recognition system specifically designed for MSL. The system focuses on recognizing nine Malayalam characters used in MSL communication. The proposed system utilises a deep learning approach, employing a modified Inception V4 model, for accurate image classification and character identification. The recognition system aims to address the communication barriers faced by individuals with hearing or speaking disabilities who rely on MSL for effective communication. The model utilises a modified Inception V4 model for image classification and letter identification, ensuring accurate recognition of Malayalam Sign Language symbols. This advancement significantly improves the communication experience for individuals who rely on sign language. Compared to other state-of-the-art methods, the proposed Inception V4 model performs better, achieving a Top-1 error rate of 17.7% and a Top-5 error rate of 3.8%.