Web based transcription editor

As technology evolves rapidly over the years, the vast majority relies on the Internet to accomplish many daily activities, such as watching videos and TV shows on video sites like YouTube. These videos may include closed captions from a transcript to help different groups of people understand the c...

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Main Author: Hew, Jun Wei Zach
Other Authors: Chng Eng Siong
Format: Final Year Project
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/69124
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Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-69124
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spelling sg-ntu-dr.10356-691242023-03-03T20:31:33Z Web based transcription editor Hew, Jun Wei Zach Chng Eng Siong School of Computer Engineering DRNTU::Engineering As technology evolves rapidly over the years, the vast majority relies on the Internet to accomplish many daily activities, such as watching videos and TV shows on video sites like YouTube. These videos may include closed captions from a transcript to help different groups of people understand the context better. However, for most of the time, the transcript is manually prepared by human transcriber(s) who listens to the audio and transcribes the voices into text form and in painstaking detail. The process is very tedious, slow and inefficient. With rapid developments in the area of Speech Recognition, Automatic Speech Recognition (ASR) systems have helped to cut down the manual transcribing work tremendously, with the utilization of deep machine learning and algorithms. However, the ASR output is never error-free due an exhaustive list of factors that can affect the audio quality which the ASR is dependent on. Human intervention is required to review the transcript and make any necessary amendments for quality assurance. In this project, I will be looking at existing transcribing tools and solutions, analysing their advantages and disadvantages, and explore different technologies that can be integrated into my proposed solution to streamline the process of editing transcripts. Bachelor of Engineering (Computer Science) 2016-11-09T01:21:25Z 2016-11-09T01:21:25Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/69124 en Nanyang Technological University 77 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
spellingShingle DRNTU::Engineering
Hew, Jun Wei Zach
Web based transcription editor
description As technology evolves rapidly over the years, the vast majority relies on the Internet to accomplish many daily activities, such as watching videos and TV shows on video sites like YouTube. These videos may include closed captions from a transcript to help different groups of people understand the context better. However, for most of the time, the transcript is manually prepared by human transcriber(s) who listens to the audio and transcribes the voices into text form and in painstaking detail. The process is very tedious, slow and inefficient. With rapid developments in the area of Speech Recognition, Automatic Speech Recognition (ASR) systems have helped to cut down the manual transcribing work tremendously, with the utilization of deep machine learning and algorithms. However, the ASR output is never error-free due an exhaustive list of factors that can affect the audio quality which the ASR is dependent on. Human intervention is required to review the transcript and make any necessary amendments for quality assurance. In this project, I will be looking at existing transcribing tools and solutions, analysing their advantages and disadvantages, and explore different technologies that can be integrated into my proposed solution to streamline the process of editing transcripts.
author2 Chng Eng Siong
author_facet Chng Eng Siong
Hew, Jun Wei Zach
format Final Year Project
author Hew, Jun Wei Zach
author_sort Hew, Jun Wei Zach
title Web based transcription editor
title_short Web based transcription editor
title_full Web based transcription editor
title_fullStr Web based transcription editor
title_full_unstemmed Web based transcription editor
title_sort web based transcription editor
publishDate 2016
url http://hdl.handle.net/10356/69124
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