Voice Activity Detection in Real-Time Speech Processing using Deep Learning

The COVID-19 has changed dramatically the educational environments in all countries over the world. Due to the pandemic, online education has played an important role over the past two years while in-person classroom teaching had to be prevented. Under the present pandemic circumstance, although a quite number of courses at many universities had being held remotely, transferring all the educational activities online would bring many issues to both trainers and trainees. One of the key issues is about the lack of an integrated advanced online learning platform with which instructors can prepare course material conveniently and efficiently. Also, the present form of online teaching is mainly based on the slides prepared before hand, which makes learners tired and bored. On the other hand, some educators offer e-courses by providing pre-recorded videos. However, these videos either present slides or make use of a traditional classroom board setup, which is not efficient either, since the instructors lack of intuitive and inspiring means of delivering the material. In this project, we aim to develop a novel intelligent speech processing system based on artificial intelligence (AI) to facilitate remote teaching.

Faculty Supervisor:

Wei-Ping Zhu

Student:

Partner:

Castofly Technologies Inc.

Discipline:

Engineering

Sector:

Information and cultural industries; Manufacturing

University:

Concordia University

Program: