INTERPRETING DOCTORS NOTES FROM TEXT TO SPEECH CONVERSION USING HTR

Computer Engineering

The ability to express language, thoughts, and ideas through handwriting. It is a widely established fact that the majority of doctors have unreadable cursive handwriting. We show the Convolutional Neural Network (CNN)-based Handwriting Recognition System in action, which was developed to recognize the text in pictures of prescriptions written by doctors and to show how cursive handwriting may be transformed into legible text. The most successful method for resolving handwriting identification issues is to use convolutional neural networks (CNNs), and they are quite proficient at identifying the structure of handwritten letters and words in ways that make it easier to automatically extract distinguishing features. Handwriting recognition (HWR) is the ability of a computer to take and interpret comprehensible handwritten input from sources such as paper documents, images, touch displays, and other devices (HTR) they are quite proficient at identifying the structure of handwritten letters and words in ways that make it easier to automatically extract distinguishing features.

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