Converting Voice Signal to Visual Indian Sign Language

Deaf people rely heavily on sign language as their primary means of communication since it is a sort of symbolic representation that they use. In contrast to sound patterns that are transferred by acoustic methods, sign language involves the employment of body posture and physical communication in order to assist the efficient presentation of a person's own phrases. When talking with those who have trouble speaking vocally, as well as with others who do not have hearing impairments, it is possible to use this method. Using developing technologies such as internet applications, machine learning, and natural language processing, the purpose of this initiative is to close the gap that exists between those who are deaf or hard of hearing or who have hearing impairments and the general community. This will be accomplished by bridging the gap between the two groups. To provide aid to those who are deaf or hard of hearing, the major aim of this project is to design a software or interface that transforms audio and speech into the proper sign language. This will be accomplished in order to provide support to such individuals. Hand forms, posture, and body actions are all in sync with one another whenever they occur at the same time. The method is made up of two distinct components: first, it converts speech into text by utilizing the voice-to-text application programming interface (API); second, it represents the text by utilizing Parse Trees and employs Natural Language Processing semantics (NLTK in particular) for the purpose of lexical analysis of Sign Language Grammar. Both of these components are a part of the method. In this work, the regulations of Indian Sign Language (ISL) are adhered to, and the work develops upon those norms while also adhering to the grammatical requirements of ISL.