Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/9022
Title: NLP Driven Adaptive Video Playback Rate Adjustment
Authors: Ozbey, Alpay Furkan
Demirtas, Ali Murat
Keywords: Multimedia playback rate adjustment
Video summarization
Extractive summarization
Natural language processing
Mmultimedia signal processing
Issue Date: 2022
Publisher: IEEE
Abstract: This paper suggests the first method to adjust video playback rate actively according to the importance of the scenes using Natural Language Processing (NLP). For this purpose, the relationship between scene information and required playback time has been formalized. We propose a data set that consists of several YouTube videos from different categories. Our learning powered model mainly relies on some statistical extractive summarization techniques and various additional features such as context-specific important words. Furthermore, we have incorporated our model with a success-proven summarization model and studied its impact on the results. Lastly, we show subjective ratings for the proposed approach, which drastically reduces the required watching time without loss of any information.
Description: 9th International Conference on Electrical and Electronics Engineering (ICEEE) -- MAR 29-31, 2022 -- Alanya, TURKEY
URI: https://doi.org/10.1109/ICEEE55327.2022.9772603
https://hdl.handle.net/20.500.11851/9022
ISBN: 978-1-6654-6754-4
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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