Over 5% of the world's population – or 430 million people – require rehabilitation to address their 'disabling' hearing loss (432 million adults and 34 million children). It is estimated that by 2050 over 700 million people – or one in every ten people – will have disabling hearing loss. The people with profound hearing loss learns sign languages but we can’t ignore the fact that not everyone in this world is comfortable with sign language. This acts as a barrier. Here we decided to work on this theme because as comparing humans and VUIs(Voice User Interfaces),the speech recognition systems are lacking milennia and contextual experience and VUIs still encounter challenges when trying to understand the semantics of sentence. With recent developments,it’s going to be interesting to see how the current challenges of speech recognition will be dealt with. So,here we are to solve all the problems now have a look on solution of these problems.

Our intention is focused on the betterment of people with profound hearing loss. Looking at the severity of the situation we think the solution should be efficient as well as user-friendly at the same time because we are dealing with a community with hearing loss.  As we know Speech recognition, or speech-to-text, is the ability of a machine or program to identify words spoken aloud and convert them into readable text.  So with the help of speech recognition  we are going to develop an Application which helps "PEOPLE WITH PROFOUND HEARING LOSS" to understand what other person is speaking with the help of texts. Our idea is, the one who can't hear can simply open the application and with one tap, the voice of the person infront of him will be converted to text, allowing the person to understand the speaker.