Irene Benedetto
Video lectures summarization.
Rel. Laura Farinetti, Lorenzo Canale, Luca Cagliero. Politecnico di Torino, Master of science program in Data Science And Engineering, 2021
|
Preview |
PDF (Tesi_di_laurea)
- Thesis
Licence: Creative Commons Attribution Non-commercial No Derivatives. Download (6MB) | Preview |
Abstract
With the recent advancements in e-learning platforms and the spread of distance learning, there is a growth in interest in generating content accompanying traditional video lessons, that seek to improve the teaching quality. In this context, the thesis analyses and proposes some approaches for the creation of a compact representation of video lectures. This thesis in analysis aims to compare different techniques that derive from the NLP and deep learning fields in order to summarize the content of video lecture transcripts. An Automatic Speech Recognition (ASR) system first generates a direct transcription from audio into text. Next, summarisation models summarise key parts of the transcription.
Text summarization and related tasks have been extensively studied in the literature, conversely, transcript summarization has not been fully explored
Relators
Academic year
Publication type
Number of Pages
Course of studies
Classe di laurea
URI
![]() |
Modify record (reserved for operators) |
