Presenter(s)

    Brad Richard Sorg

    Comments

    This poster reflects research conducted as part of a course project designed to give students experience in the research process.

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    Description

    The semantic interpretation of the human language is very complex and diverse making natural language processing an interesting task for researchers and engineers. Natural language processing is a subfield of machine learning focusing on enabling computers to understand and process human languages. Although computers do not have the same intuitive understanding of natural language like humans do, recent advances in machine learning have enabled computers to perform many useful things with natural language like text classification, language modeling, speech recognition, and question answering. Computers are able to accomplish these tasks by learning the deep contextual representations of words including both the syntax and semantics. Through the use of recurrent neural networks, long short-term memory units, temporal convolution networks, and different language embedding models, computers have made significant strides in their ability to interpret and understand human language. With large volumes of textual data available and the need to structure the unstructured data source that is human language, the area of natural language processing will continue to be of interest.

    Publication Date

    4-24-2019

    Project Designation

    Course Project

    Primary Advisor

    Vijayan K. Asari

    Primary Advisor's Department

    Electrical and Computer Engineering

    Keywords

    Stander Symposium project

    Natural Language Processing: A Look Into How Computers Understand Human Language

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