English sentence unit detection based on text features

Sentence unit detection in automated speech recognition (ASR) system is crucial for enriching the ASR output, improving the human readability, processing the word stream of the output and bridging the gap between the ASR system with the NLP applications.This thesis presents the machine learning mode...

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Main Author: Stephanie
Other Authors: Chng Eng Siong
Format: Final Year Project
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/66649
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-666492023-03-03T20:44:11Z English sentence unit detection based on text features Stephanie Chng Eng Siong School of Computer Engineering Emerging Research Lab DRNTU::Engineering::Computer science and engineering Sentence unit detection in automated speech recognition (ASR) system is crucial for enriching the ASR output, improving the human readability, processing the word stream of the output and bridging the gap between the ASR system with the NLP applications.This thesis presents the machine learning models for sentence unit detection in written text. In this context, sentence unit (SUs) is referred to punctuation marks in the sentence, in which the focus is on adding period (“.”) to the unstructured word sequence. Bachelor of Engineering (Computer Science) 2016-04-20T04:49:27Z 2016-04-20T04:49:27Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/66649 en Nanyang Technological University 48 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Stephanie
English sentence unit detection based on text features
description Sentence unit detection in automated speech recognition (ASR) system is crucial for enriching the ASR output, improving the human readability, processing the word stream of the output and bridging the gap between the ASR system with the NLP applications.This thesis presents the machine learning models for sentence unit detection in written text. In this context, sentence unit (SUs) is referred to punctuation marks in the sentence, in which the focus is on adding period (“.”) to the unstructured word sequence.
author2 Chng Eng Siong
author_facet Chng Eng Siong
Stephanie
format Final Year Project
author Stephanie
author_sort Stephanie
title English sentence unit detection based on text features
title_short English sentence unit detection based on text features
title_full English sentence unit detection based on text features
title_fullStr English sentence unit detection based on text features
title_full_unstemmed English sentence unit detection based on text features
title_sort english sentence unit detection based on text features
publishDate 2016
url http://hdl.handle.net/10356/66649
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