2nd International Workshop on
Multimodal Conversational AI
Recently, conversational systems have seen a significant rise in demand due to modern commercial applications using systems such as Amazon's Alexa, Apple's Siri, Microsoft's Cortana and Google Assistant. The research on multimodal chatbots is a widely underexplored area, where users and the conversational agent communicate by natural language and visual data.
Conversational agents are now becoming a commodity as a number of companies push for this technology. The wide use of these conversational agents exposes the many challenges in achieving more natural, human-like, and engaging conversational agents. The research community is actively addressing several of these challenges: how are visual and text data related in user utterances? How to interpret the user intent? How to encode multimodal dialog status? What are the ethical and legal aspects of conversational AI?
The Multimodal Conversational AI workshop will be a forum where researchers and practitioners share their experiences and brainstorm about success and failures in the topic. It will also promote collaboration to strengthen the conversational AI community at ACM Multimedia.
We welcome contributions that are not limited algorithmic advances in the area:
hands-on experience
position papers
open source efforts
frameworks
Important dates:
Submission deadline: August 10
Notifications: September 2
Camera ready: September 10
Workshop: October 20
Keynote speaker:
Alborz Geramifard, Facebook
Panel:
(Moderator) Alex Hauptmann, CMU
Zhenzhong Lan, Westlake University
Alex Rudnicky, CMU/LTI
Ben Sauer,
Melissa Lim, Farfetch
Topics
Design and evaluation of conversational agents
User-Agent experience design
Preference elicitation in conversational agents
Recommendations in conversational systems
User-agent legal and ethical issues in conversational systems
Multimodal user intent understanding
Visual conversations/dialogs
Opinion recommendation in conversational agents
Deep learning for multimodal conversational agents
Conversation state tracking models and online learning
Supply/demand in conversational agents for e-commerce
Reinforcement learning in conversational agents
Resources and datasets
Conversational systems applications, including, but not limited to, e-commerce, social-good, music, Web search, healthcare.