Visualization Techniques in Text Summarization of Online Transcripts – Students’ Research in ML and DL at Durham College

Text summarization is a method for generating a summary of long texts by focusing on the sections that contain essential information while keeping the overall meaning intact. Its goal is to reduce the size of long documents, which would be difficult and expensive to process manually. With the current explosion of data circulating in digital space, particularly unstructured textual data, there is a need to build tools that allow people to extract insights from it. Taking notes is a popular practice for many people employed in situations where it is essential to keep track of what is said, such as during an online lecture. The art of note-taking does not entail taking down every single word stated but rather broad summaries of what is covered. Making succinct yet informative summaries is the key to successful note-taking. In this seminar, we will be discussing how we have used visualization and data storytelling techniques in our project to make informed decisions. This project aims to address the difficulties of note-taking by building an application that produces notes based on the transcripts generated by the Automatic Speech Recognition (ASR) technology of the meeting platforms. We relied on visualization concepts for three major decisions that would define our project as a whole. These decisions are the choice of online meeting platform, preference of text summarization model and the messaging platform choice.

Speaker(s): Manoj Varma Alluri, Navaneeth Jawahar, Sharath Kumar Prabhu, Jeel Jani

Register: https://events.vtools.ieee.org/m/313207