Learning to Dialogue with Machines
Achieving human-machine dialogue is often considered the very definition of artificial intelligence. Deep-learning has resulted in large improvements in speech recognition, but there are still barriers to overcome before true conversation is realised. A conversational system must also understand what was said, adjust for context, decide what to say and decide how to say it. VocalIQ builds technology to solve all of these tasks with machine learning. This talk will discuss some of the issues involved.
Before co-founding VocalIQ, Blaise spent several years researching new approaches to building spoken dialogue systems; first as part of his Ph.D. and then as a Research Fellow at the University of Cambridge. Many of these new ideas are integrated into VocalIQ technology and have been awarded prizes within the research community.
Specifically, Dr. Thomson has received multiple awards from the IEEE and the Journal of Computer Speech and Language for his groundbreaking research into natural language processing and machine learning algorithm design.
He received a BSc(Hons), Pure Mathematics, 1st, from the University of Cape Town, South Africa in 2004. Outside of work, he enjoys playing guitar and dancing.