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.