A Deep Insight in Challenges of Natural Language Processing and Usage of Deep Learning
Varsha Mittal1, Durgaprasad Gangodkar2, Bhaskar Pant3, Nisha Chandran4
1Varsha Mittal, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun (Uttarakhand), India.
2Durgaprasad Gangodkar, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun (Uttarakhand), India.
3Bhaskar Pant, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun (Uttarakhand), India.
4Nisha Chandran, Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun (Uttarakhand), India.
Manuscript received on 15 June 2020 | Revised Manuscript received on 26 June 2020 | Manuscript Published on 04 July 2020 | PP: 50-54 | Volume-8 Issue-12S3 October 2019 | Retrieval Number: L101410812S319/2020©BEIESP | DOI: 10.35940/ijitee.L1014.10812S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Natural Language Processing (NLP) using the power of artificial intelligence has empowered the understanding of the language used by human. It has also enhanced the effectiveness of the communication between human and computers. The complexity and diversity of the huge datasets have raised the requirement for automatic analysis of the linguistic data by using data-driven approaches. The performance of the data-driven approaches is improved after the usage of different deep learning techniques in various application areas of NLP like Automatic Speech Recognition, POS tagging etc. The paper addresses the challenges faced in NLP and the use of deep learning techniques in different application areas of NLP.
Keywords: Artificial Intelligence, Deep Learning, Natural Language Processing; Machine Learning.
Scope of the Article: Deep Learning