Keyword and named entity recognition on air traffic control text

Aviation safety is utmost critical to ensure that passengers and flight crew are safe while in flight. Safety always comes first as lives are involved on every flight. It has always been the most important aspect of air travel. Past incidents of miscommunication between pilots and air traffic contro...

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Main Author: Tay, Nikole Qiwei
Other Authors: Chng Eng Siong
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/144503
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1445032020-11-10T02:06:05Z Keyword and named entity recognition on air traffic control text Tay, Nikole Qiwei Chng Eng Siong School of Computer Science and Engineering ASESChng@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Computer science and engineering::Computing methodologies::Document and text processing Aviation safety is utmost critical to ensure that passengers and flight crew are safe while in flight. Safety always comes first as lives are involved on every flight. It has always been the most important aspect of air travel. Past incidents of miscommunication between pilots and air traffic controllers had resulted in ill-fated accidents that could have been prevented. It is therefore crucial that we uncover solutions to prevent mishaps from occurring in the skies and at airports. This report will discuss the application of Named Entity Recognition (NER), a Natural Language Processing (NLP) method on Air Traffic Control (ATC) conversations to improve and attain higher precision in the communication between pilots and air traffic controllers. An ATC dataset will be generated based on grammar rules through the usage of OpenFST and the Thrax Compiler. Thereafter, this ATC dataset will be used to train a model using a Bi-LSTM-CRF based NER system. A demo website which allows the input of ATC text features the working application of NER by returning the highlighted and annotated name entities. Bachelor of Engineering (Computer Science) 2020-11-10T02:06:05Z 2020-11-10T02:06:05Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/144503 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Engineering::Computer science and engineering::Computing methodologies::Document and text processing
spellingShingle Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Engineering::Computer science and engineering::Computing methodologies::Document and text processing
Tay, Nikole Qiwei
Keyword and named entity recognition on air traffic control text
description Aviation safety is utmost critical to ensure that passengers and flight crew are safe while in flight. Safety always comes first as lives are involved on every flight. It has always been the most important aspect of air travel. Past incidents of miscommunication between pilots and air traffic controllers had resulted in ill-fated accidents that could have been prevented. It is therefore crucial that we uncover solutions to prevent mishaps from occurring in the skies and at airports. This report will discuss the application of Named Entity Recognition (NER), a Natural Language Processing (NLP) method on Air Traffic Control (ATC) conversations to improve and attain higher precision in the communication between pilots and air traffic controllers. An ATC dataset will be generated based on grammar rules through the usage of OpenFST and the Thrax Compiler. Thereafter, this ATC dataset will be used to train a model using a Bi-LSTM-CRF based NER system. A demo website which allows the input of ATC text features the working application of NER by returning the highlighted and annotated name entities.
author2 Chng Eng Siong
author_facet Chng Eng Siong
Tay, Nikole Qiwei
format Final Year Project
author Tay, Nikole Qiwei
author_sort Tay, Nikole Qiwei
title Keyword and named entity recognition on air traffic control text
title_short Keyword and named entity recognition on air traffic control text
title_full Keyword and named entity recognition on air traffic control text
title_fullStr Keyword and named entity recognition on air traffic control text
title_full_unstemmed Keyword and named entity recognition on air traffic control text
title_sort keyword and named entity recognition on air traffic control text
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/144503
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