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 proceedingConference 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 languageEnglish
    Title of host publicationProceedings - 2010 IEEE international conference on intelligent computing and intelligent systems, ICIS 2010
    Place of PublicationNew York
    PublisherIEEE
    Pages488-492
    ISBN (Print)9781424465828
    DOIs
    Publication statusPublished - 6 Dec 2010
    Event2010 IEEE International Conference on Intelligent Computing and Intelligent Systems - Xiamen, China
    Duration: 29 Oct 201031 Oct 2010

    Conference

    Conference2010 IEEE International Conference on Intelligent Computing and Intelligent Systems
    Abbreviated titleICIS 2010
    CountryChina
    CityXiamen
    Period29/10/1031/10/10

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  • Cite this

    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 (pp. 488-492). IEEE. https://doi.org/10.1109/ICICISYS.2010.5658266