HearingHands : Amplifying the Voices of Deaf Community

Natural language, sign language employs several modes of expression for everyday communication. Researchers have paid less attention to ISL interpretation than other forms of sign language. This paper introduces an automatic technique for translating manual letter movements into Hindi sign language. Because it works with pictures of bare hands, the user may interact with the device naturally. System gives deaf individuals the chance to interact with hearing people without the use of an interpreter. This paper goal is to develop techniques and a system for automatically recognizing Hindi sign language. The creation of a Hindi Sign Language database is the initial stage in this system. The most important stage in any hand gesture recognition system is hand segmentation since higher recognition rates may be attained with better segmented output. To improve identification rates, the suggested system additionally incorporates reliable and effective hand segmentation and tracking algorithms. Using a large sample set, it has been shown to be feasible to recognise 43 different words from the Standard Hindi sign language. We want to be able to convert certain very basic parts of sign language into text in the suggested system and vice versa in Hindi. In this paper, we present a number of new features and prospective advancements:The emphasis on real-time systems that recognize and interpret sign language motions from live video input is one noteworthy advance. With the use of this feature, people who use sign language and others can communicate instantly without any delays or middlemen. Integration of Speech Synthesis and Hand Gesture Recognition: This innovative approach to communication accessibility combines speech synthesis and hand gesture recognition technology. The paper provides a comprehensive solution for promoting engagement and understanding between the deaf community and others who communicate primarily through spoken language by translating gestures from sign language into intonation-rich speech.