Open-Ended Challenges in Dialog Systems
Dialog Systems have come a long way, especially with advancements brought by assistants such as Alexa. However, there are several open-ended challenges which makes it hard to build fully Conversational Dialog Systems. In this talk, I will go over some of these open-ended challenges and discuss how to address them.
Chandra Khatri is a Senior AI Scientist at Uber AI driving Conversational AI efforts at Uber. Prior to Uber, he was the Lead AI Scientist at Alexa and was driving the Science for the Alexa Prize Competition, which is a $3.5 Million university competition for advancing the state of Conversational AI. Some of his recent work involves Open-domain Dialog Planning and Evaluation, Conversational Speech Recognition, Conversational Natural Language Understanding, and Sequential Modeling.
Prior to Alexa, Chandra was a Research Scientist at eBay, wherein he led various Deep Learning and NLP initiatives such as Automatic Text Summarization and Automatic Content Generation within the eCommerce domain, which has lead to significant gains for eBay. He holds degrees in Machine Learning and Computational Science & Engineering from Georgia Tech and BITS Pilani.