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Analysing Oral Presentation Quality: A Multimodal Approach Incorporating Presentation Delivery and Slide Quality

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dc.contributor.author Wanigasinghe, Naween
dc.date.accessioned 2025-06-30T09:22:16Z
dc.date.available 2025-06-30T09:22:16Z
dc.date.issued 2024
dc.identifier.citation Wanigasinghe, Naween (2024) Analysing Oral Presentation Quality: A Multimodal Approach Incorporating Presentation Delivery and Slide Quality. Msc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 20221917
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/2783
dc.description.abstract "This research addresses the challenge of enhancing presentation skills through the development of a mobile-responsive web application called 'Presently'. The app aims to help speakers improve pronunciation, vocabulary, emotional expression, and slide quality. It provides users with personalized feedback to enhance their presentation delivery. The methodology employed involves the use of automatic speech recognition (ASR) for pronunciation and vocabulary analysis, audio and video analysis for emotion and tone detection, and computer vision for slide quality assessment. The app utilizes machine learning algorithms to provide users with tailored suggestions for improvement based on their performance. Initial testing of the 'Presently' prototype shows promising results. For face emotion detection component achieved an accuracy rate of 74.2%. Emotion and tone detection in audio analysis reached an accuracy rate of 95.6%. Slide quality assessment using computer vision techniques showed global recognized standards in identifying content accuracy and aesthetics." en_US
dc.language.iso en en_US
dc.subject Automatics speech recognition en_US
dc.subject Emotion detection en_US
dc.subject Computer vision en_US
dc.title Analysing Oral Presentation Quality: A Multimodal Approach Incorporating Presentation Delivery and Slide Quality en_US
dc.type Thesis en_US


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