Artificial Neural Networks based DIGI Writing

There has been a lot of progress in the development of machine learning for us to develop the understandings of the machinery mind. As humans, we learn how to do a task by doing it, and optimize the tasks by learning from our mistakes. Machines can comprehend situations of strengthening developed neurons in the same way that neurons in the brain automatically trigger and quickly perform learned tasks. Deep learning is as intriguing as the concept of the human brain. The use of various types of architectures for such neural networks collides for various types of problems, such as image and sound classification, object recognition, image segmentation, object detection, and so on. Following these layers of different commemorations and accuracy that Artificial Intelligence provides, many unsolved issues can be solved here by one machine, problems, and tasks, because the machine is now capable of approaching the task as if it’s thought process is as same as that of a human brain with a precise accuracy. The proposed work focuses on the development in speech applications that will scan the input which is basically a specific image and will give an audio output of the given input. Embedding CNN and RNN has produced promising results with good accuracy.