Zoom: https://illinois.zoom.us/j/89379675276?pwd=SWM5Z1gxWkdSVUtkQXBvMDk1MUQwQT09
Abstract:
Following the recent advancements in language modeling and availability of large natural language datasets, the last decade has been flourishing for conversational AI research. The progress also helped emphasize the importance of reasoning over a diverse set of external knowledge and task completion resources for forming relevant, informative, and accurate responses, discussing with the users when the available solutions/information are not sufficient, and making proactive suggestions.
For ingesting knowledge in conversations, recent work has mainly grounded conversational responses on knowledge snippets from wikipedia and web documents, with the goals of preventing hallucination and providing users diverse and accurate responses. However, much of the world's knowledge is dynamic and it is spread across diverse resources. Some of these are already structured, such as knowledge graphs. But a majority of them are not structured, for example, news articles and books. And some of them also include subjective information, such as customer reviews. In this talk, I will discuss our recent work on integrating knowledge to conversation responses from such a diverse set of resources, challenges associated with these, and progress we made so far.
I will conclude by summarizing the remaining challenges towards conversational assistants.
Bio:
Dilek Hakkani-Tür is a researcher focusing on enabling natural dialogues with machines. She worked as a research scientist at Amazon Alexa AI, Google Research, Microsoft Research, International Computer Science Institute at University of California, Berkeley, and AT&T Labs - Research. She received her BSc degree from Middle East Technical Univ, and MSc and PhD degrees from Bilkent Univ, Department of Computer Engineering. Her research interests include conversational AI, natural language and speech processing, spoken dialogue systems, and machine learning for language processing. She has over 80 patents that were granted and co-authored more than 300 papers in natural language and speech processing. She received several best paper awards for publications she co-authored, from IEEE Signal Processing Society, ISCA, EURASIP and others. She served as an associate editor for IEEE Transactions on Audio, Speech and Language Processing (2005-2008), a member of the IEEE Speech and Language Technical Committee (2009-2014), an area editor for speech and language processing for Elsevier's Digital Signal Processing Journal and IEEE Signal Processing Letters (2011-2013), the Editor-in-Chief of the IEEE/ACM Transactions on Audio, Speech and Language Processing (2018-2021), and an IEEE Distinguished Industry Speaker (2021). She also served on the ISCA Advisory Council (2015-2018) and the IEEE Signal Processing Society Fellows Committee (2019-2022). She was elected as a fellow of the IEEE (2014) and ISCA (2014).
Faculty Host: Heng Ji
Meeting ID: 893 7967 5276; Password: csillinois
