Handwritten Script Detection and Translation

Humans are aware about English language which has been prevalent since the times of British era. But still difficulty is faced in by the people who only stick to their native language or are so proud of their native language that they tend to use them everywhere be it in marketing, teaching, business deals etc. English has established its percentage to around twenty in total languages that is spoken and that is used for business purpose only. But in country like India the use of native language seems to play a role on a wider scale. Use cases of recognizing and translating has reached into the fields like healthcare and pharmaceutical, insurance, banking, online libraries. This led people to understand the need for translating a particular text into their preferred language for better understanding be it any field. An attempt is made to recognize the given text and followed by its translation into preferred language using a designed dataset. Wherein the detection of the text is performed by using Convolutional Neural Network (CNN), and other neural networks that is required for full processing of the text recognized image and led to the desired output. The model detects the language of the given text and next leads to translation of the given text into the native language. This flow will ease down the recognition of handwritings written in different way and will help to reduce labor cost and save precious human time.