An Interpreter for the Differently Abled using Haptic Feedback and Machine Learning

One of the most valuable blessings to humanity is the ability to see, hear, talk and respond according to the situation. However, some people are deprived of this, such as the differently-abled community who find it hard to communicate and hence they are permanently dependent on someone. To overcome this dependency and to bridge the communication barrier of such deprived, an interpreter can be used. This work proposes an Interpreter system which enables two-way communication between the common people and the differently-abled regardless of the kind of sensory disability the user has. The system implemented has two modules - an American Sign Language recognition module which uses a machine-learning algorithm to cater the people with vocal disability and a speech to haptic feedback conversion module which can be used for communicating to any kind of differently-abled. Both these modules can be integrated together as a single compact device to address the communication barrier between different combinations of disabled people.