Natural Language Generation Using Machine Learning Techniques

Authors

  • Angelina Yang Plano West Senior High School
  • Sadaf Halim University of Texas at Dallas

DOI:

https://doi.org/10.47611/jsrhs.v11i2.3342

Keywords:

Artificial Intelligence, Machine Learning, Language Generation, Neural Networks

Abstract

Natural language generation is a subfield of machine learning, consisting of creating systems that can produce understandable texts in the human language. It is applied to all areas dealing with reporting and content creation, such as journalism and online chatbots. Despite natural language generation being labeled as a subfield, it covers a vast range of topics beyond the scope of this paper. Instead, this research paper aims to provide an overview on select topics within natural language generation: Word Embedding, Long Short-Term Memory (LSTM), and Encoder-Decoder Architecture. The authors have analyzed and reinterpreted so that the audience has an improved understanding of natural language generation in spite of the topic’s broad reach.

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References or Bibliography

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Published

05-31-2022

How to Cite

Yang, A., & Halim, S. (2022). Natural Language Generation Using Machine Learning Techniques. Journal of Student Research, 11(2). https://doi.org/10.47611/jsrhs.v11i2.3342

Issue

Section

HS Review Articles