Effective communication facilitates the sharing of emotions, expressions, and thoughts among individuals, thereby fostering stronger interpersonal connections. There are around 5% of the population of the world who suffer Deaf or hearing-impaired. Complex arm movements with articulated hand forms and facial expressions are used for this purpose. However, the scope for them to communicate with normal people is limited. Our objective is to leverage technology to address this communication gap. To achieve this goal, we present a sophisticated framework in this paper that integrates sign language with cutting-edge machine learning and deep learning techniques. By utilizing the capabilities of Media pipe and TensorFlow with Python, our framework's robustness is significantly improved.Custom made data set is hybridized with American sign language data set during the experimentation. Experimentation results are encouraging with an accuracy of 93%. Our approach holds significant promise in facilitating communication for those with hearing impairment and can lead to a more inclusive society.