Exposing knowledge in speech: Monitoring conceptual development in spoken conversation

Ruben Lagatie, Fridolin Wild, Patrick De Causmaecker, Peter Scott

    Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

    2 Citations (Scopus)


    Automatic evaluation of verbal activities has always been hard. On the one hand, teachers want to stimulate student engagement and therefore often base grades on the number of participations. On the other hand, if quantity is more important than quality, students might participate, but add nothing new to the conversation. Providing feedback for spoken conversations is another challenge, one that is often solved by doing things manually. Both aspects originate from the same problem, the difficulty of extracting semantic knowledge from speech. In this contribution we present our approach to extracting and visualising this semantic knowledge using an open source speech recognition engine and Latent Semantic Analysis.

    Original languageEnglish
    Title of host publication2011 IST-Africa Conference Proceedings, IST 2011
    Publication statusPublished - 2011
    Event2011 IST-Africa Conference, IST 2011 - Gaborone, Botswana
    Duration: 11 May 201113 May 2011

    Publication series

    Name2011 IST-Africa Conference Proceedings, IST 2011


    Conference2011 IST-Africa Conference, IST 2011


    • Automatic Speech Recognition
    • Conceptual diagram
    • Knowledge Representation
    • Latent Semantic Analysis
    • Topic Spotting


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