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A Survey of Text Generation Models

by Mayuresh Muley, Pruthav Sanwatsarkar, Vrushali Kulkarni
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 21
Year of Publication: 2022
Authors: Mayuresh Muley, Pruthav Sanwatsarkar, Vrushali Kulkarni
10.5120/ijca2022922247

Mayuresh Muley, Pruthav Sanwatsarkar, Vrushali Kulkarni . A Survey of Text Generation Models. International Journal of Computer Applications. 184, 21 ( Jul 2022), 65-71. DOI=10.5120/ijca2022922247

@article{ 10.5120/ijca2022922247,
author = { Mayuresh Muley, Pruthav Sanwatsarkar, Vrushali Kulkarni },
title = { A Survey of Text Generation Models },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2022 },
volume = { 184 },
number = { 21 },
month = { Jul },
year = { 2022 },
issn = { 0975-8887 },
pages = { 65-71 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number21/32444-2022922247/ },
doi = { 10.5120/ijca2022922247 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:22:05.302074+05:30
%A Mayuresh Muley
%A Pruthav Sanwatsarkar
%A Vrushali Kulkarni
%T A Survey of Text Generation Models
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 21
%P 65-71
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Natural language processing (NLP)is a field of linguistics and computer science which focuses on the interaction of humans and computers. The main aim of natural language processing is to make sure that a computer can understand what a human says and possibly get key insights from the auditory data. Natural language text production is a well-known sub-part of NLP which focuses on converting auditory data from spoken languages into text. This survey aims to shed some light on crucial details about the past, present and the future of text production algorithms along with an aim to provide a comprehensive overview of how different machine learning techniques are being investigated and studied for different NLP applications. Finally, some important research gaps which were found out through the review are highlighted as the study is drawn to a close. This study also aims to synthesize a guide for beginners in this field and to point them towards related research and popular practices.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Text generation Markov chains LSTM NLP Deep learning techniques

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