• Balivada Sai Sree
• Gudiwaka Vijayalakshmi

Sign language recognition is a complex task that involves a wide range of fields, such as computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and Deaf culture. Sign language is a primary mode of communication for the speech and hearing-impaired community, and for those who are not familiar with sign language, communicating without an interpreter can be difficult. Sign language recognition involves tracking and recognizing the meaningful gestures made by the human body, including head, arms, hands, fingers, and facial expressions.One technique used to facilitate communication between sign language users and non-sign language users is to translate sign language gestures into spoken language, which can be easily understood by listeners. This is particularly important for people who rely solely on gestural sign language for communication and need to communicate with someone who does not understand sign language.However, most sign language recognition systems face challenges in recognizing gestures accurately, particularly when it comes to variations in skin tone. To address this issue, filters can be introduced to help identify symbols regardless of skin tone.One popular approach for sign language recognition is to use convolutional neural networks (CNNs), which consist of four types of layers: convolution layers, pooling/subsampling layers, nonlinear layers, and fully connected layers. The purpose of these layers is to represent features that the system can learn and use to recognize sign language gestures accurately.In summary, sign language recognition is a complex task that requires expertise in multiple fields. The goal is to create systems that accurately recognize sign language gestures and can translate them into spoken language to facilitate communication between sign language users and non-sign language users.

Sign Language, Hand Gesture, Speech Recognition, Deaf and dump

"Python-based Action Recognition for Detecting Sign Language", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.i1-i8, March-2023, Available :http://www.jetir.org/papers/JETIR2303801.pdf

"Python-based Action Recognition for Detecting Sign Language", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppi1-i8, March-2023, Available at : http://www.jetir.org/papers/JETIR2303801.pdf