Improving the editing process of automatically produced lecture transcripts based on Natural Language Analysis

Miltiades Papadopoulos; Elaine Pearson

doi:10.1109/ICICISYS.2010.5658266

Improving the editing process of automatically produced lecture transcripts based on Natural Language Analysis

Miltiades Papadopoulos, Elaine Pearson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Automatically produced lecture transcripts can act as an alternative to traditional note taking, benefiting those students whose needs and preferences are not met in the traditional learning environment. Nonetheless, despite the substantial progress that has been made in the area of Automatic Speech Recognition (ASR), the performance of ASR systems is still below the levels required for accurate transcription of lectures. This paper describes the development of a tool, which facilitates the evaluation of automatically produced transcription files, based on Natural Language Analysis. This tool is a step forward in the production of meaningful materials for disabled students, with minimal investment in time and effort by academic staff, thereby improving the accessibility of traditional teaching methodologies.

Original language	English
Title of host publication	Proceedings - 2010 IEEE international conference on intelligent computing and intelligent systems, ICIS 2010
Place of Publication	New York
Publisher	IEEE
Pages	488-492
ISBN (Print)	9781424465828
DOIs	https://doi.org/10.1109/ICICISYS.2010.5658266
Publication status	Published - 6 Dec 2010
Event	2010 IEEE International Conference on Intelligent Computing and Intelligent Systems - Xiamen, China Duration: 29 Oct 2010 → 31 Oct 2010

Conference

Conference	2010 IEEE International Conference on Intelligent Computing and Intelligent Systems
Abbreviated title	ICIS 2010
Country/Territory	China
City	Xiamen
Period	29/10/10 → 31/10/10

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10.1109/ICICISYS.2010.5658266

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http://ieeexplore.ieee.org/document/5658266/

Cite this

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title = "Improving the editing process of automatically produced lecture transcripts based on Natural Language Analysis",

abstract = "Automatically produced lecture transcripts can act as an alternative to traditional note taking, benefiting those students whose needs and preferences are not met in the traditional learning environment. Nonetheless, despite the substantial progress that has been made in the area of Automatic Speech Recognition (ASR), the performance of ASR systems is still below the levels required for accurate transcription of lectures. This paper describes the development of a tool, which facilitates the evaluation of automatically produced transcription files, based on Natural Language Analysis. This tool is a step forward in the production of meaningful materials for disabled students, with minimal investment in time and effort by academic staff, thereby improving the accessibility of traditional teaching methodologies.",

author = "Miltiades Papadopoulos and Elaine Pearson",

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publisher = "IEEE",

note = "2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010 ; Conference date: 29-10-2010 Through 31-10-2010",

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Papadopoulos, M & Pearson, E 2010, Improving the editing process of automatically produced lecture transcripts based on Natural Language Analysis. in Proceedings - 2010 IEEE international conference on intelligent computing and intelligent systems, ICIS 2010. IEEE, New York, pp. 488-492, 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, Xiamen, China, 29/10/10. https://doi.org/10.1109/ICICISYS.2010.5658266

Improving the editing process of automatically produced lecture transcripts based on Natural Language Analysis. / Papadopoulos, Miltiades; Pearson, Elaine.
Proceedings - 2010 IEEE international conference on intelligent computing and intelligent systems, ICIS 2010. New York: IEEE, 2010. p. 488-492.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - Automatically produced lecture transcripts can act as an alternative to traditional note taking, benefiting those students whose needs and preferences are not met in the traditional learning environment. Nonetheless, despite the substantial progress that has been made in the area of Automatic Speech Recognition (ASR), the performance of ASR systems is still below the levels required for accurate transcription of lectures. This paper describes the development of a tool, which facilitates the evaluation of automatically produced transcription files, based on Natural Language Analysis. This tool is a step forward in the production of meaningful materials for disabled students, with minimal investment in time and effort by academic staff, thereby improving the accessibility of traditional teaching methodologies.

AB - Automatically produced lecture transcripts can act as an alternative to traditional note taking, benefiting those students whose needs and preferences are not met in the traditional learning environment. Nonetheless, despite the substantial progress that has been made in the area of Automatic Speech Recognition (ASR), the performance of ASR systems is still below the levels required for accurate transcription of lectures. This paper describes the development of a tool, which facilitates the evaluation of automatically produced transcription files, based on Natural Language Analysis. This tool is a step forward in the production of meaningful materials for disabled students, with minimal investment in time and effort by academic staff, thereby improving the accessibility of traditional teaching methodologies.

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SP - 488

EP - 492

BT - Proceedings - 2010 IEEE international conference on intelligent computing and intelligent systems, ICIS 2010

PB - IEEE

CY - New York

T2 - 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems

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ER -

Improving the editing process of automatically produced lecture transcripts based on Natural Language Analysis

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