Explore –Journal of Research
Peer Reviewed Journal
ISSN 2278–0297 (Print)
ISSN 2278–6414 (Online)
Vol. XIV No. 2, 2022
© Patna Women’s College, Patna, India
A Survey of the Natural Language Processing using Artificial Intelligence
Priyanka R. Hipparkar
Received : April 2022
Accepted : May 2022
Corresponding Author : Priyanka R. Hipparkar
Abstract : One of the essential and effortless artificial intelligence methods that can be considered, Natural Language Processing can communicate in simple languages like English. Natural Language Understanding (NLU) helps the machine understand and analyze human language by extracting metadata from content such as concepts, existence, keywords, emotions, relationships, and semantic roles. We have briefly explained how natural language processing works and what are the components of the natural language process, and why natural language process is essential. After experimenting with thousands of recurring neural network architectures, it is found that a recurring neural network architecture can surpass both long-term memory and gated recurrent units. Concurrent neural network-based methods take longer to train than recurrent neural networks Natural Language Processing (NLP). NLP is a sub-field of artificial intelligence and with a strong focus on research and development, the research focus in in the areas of
communication systems, language processing, machine translation. Education develops many tools for creating industrial applications. The natural language process is a branch of artificial intelligence that analyzes, understands, and creates the languages that humans naturally use to communicate with computers in both written and spoken contexts, using natural human language instead of computer language. While the role of natural language processing techniques in education is being underlined, more experiments with different teaching techniques are expected. Natural language can improve the efficiency and accuracy of the process. Syntactic analysis process so that the model can capture and use more historical information.
Keywords : Artificial Intelligence, Natural Language Processing, Deep Learning, Machine Learning, Pattern Recognition.