  Task-oriented Dialogue (TOD) Systems aim to build dialogue systems that
assist users in accomplishing specific goals, such as booking a hotel or a
restaurant. Traditional TODs rely on domain-specific APIs/DBs or external
factual knowledge to generate responses, which cannot accommodate subjective
user requests (e.g., "Is the WIFI reliable?" or "Does the restaurant have a
good atmosphere?"). To address this issue, we propose a novel task of
subjective-knowledge-based TOD (SK-TOD). We also propose the first
corresponding dataset, which contains subjective knowledge-seeking dialogue
contexts and manually annotated responses grounded in subjective knowledge
sources. When evaluated with existing TOD approaches, we find that this task
poses new challenges such as aggregating diverse opinions from multiple
knowledge snippets. We hope this task and dataset can promote further research
on TOD and subjective content understanding. The code and the dataset are
available at https://github.com/alexa/dstc11-track5.
