There is always a big influence of robotics and natural language processing in the field of automation. The current scenario of natural language processing (NLP) focuses on machine analysis and machine interpretation. By the term machine analysis, accuracy becomes an important phenomenon. So, it is named Augean that refers to higher accuracy for natural language processing which is difficult to attain involving the use of neural networks. Thus far named as Augean artificial neural network. It is one of the key branches of machine learning which is peculiar from the other branches speculating more towards artificial intelligence. NLP is now one of the key aspects in making machine learn and letting it speak. The current framework of these discusses more of deep learning. One of the biggest challenges is to make the machine learn and speak is known. Thus far processing becomes the most crucial part. Therefore, when it comes to processing there is no better idea than the brain to be involved. Now the current scenario is about making machine learn to the best of the accuracy and if there is something of great accuracy then it involves a real complex algorithm. The machine works possibly best only if the accuracy stays high and stepping on to the precision of work with better learning ability machines are remarkable. So, to frame this, artificial neural network and neuroscience have been used to make the model more robust increasing the accuracy with at least five percent to the previous models involved. © 2020 IEEE.