An Overview of the Eighth Dialog System Technology Challenge
Research competitions have been a long-standing and valuable tradition in the speech and language community. They accelerate the development of new technologies by establishing a shared testbed, cross-validating many potential approaches, and attracting new researchers to the field. DSTC, the Dialog System Technology Challenge, has been a premier research competition for dialog systems since its inception in 2013. This talk presents an overview of the Eighth Dialog System Technology Challenge (DSTC8). In line with recent editions of the challenges, the eighth edition focuses on applying end-to-end dialog technologies in a pragmatic way for multi-domain task-completion, noetic response selection, audio visual scene-aware dialog, and schema-guided dialog state tracking tasks. This talk describes the task definition, provided datasets, and evaluation set-up for each track and summarizes the results of the submitted systems from the participants.
Seokhwan Kim is currently a senior machine learning scientist at Amazon Alexa AI. He received his Ph.D. from Pohang University of Science and Technology. Prior to joining Amazon, he conducted work in natural language understanding and spoken dialog systems where he was a Research Scientist at Adobe Research and the Institute for Infocomm Research. He has authored more than 50 peer-reviewed publications in international journals and conferences in speech and language technology areas. In 2015, he joined the organizing team of Dialog System Technology Challenge (DSTC) and has contributed to the last five challenges. In addition, he has been acting as a program committee member of the major conferences in NLP, speech, dialog, and AI fields including ACL, NAACL-HLT, EMNLP, ICASSP, Interspeech, IWSDS, AAAI, IJCAI, and ICLR.