  Most existing dialogue corpora and models have been designed to fit into 2
predominant categories : task-oriented dialogues portray functional goals, such
as making a restaurant reservation or booking a plane ticket, while
chit-chat/open-domain dialogues focus on holding a socially engaging talk with
a user. However, humans tend to seamlessly switch between modes and even use
chitchat to enhance task-oriented conversations. To bridge this gap, new
datasets have recently been created, blending both communication modes into
conversation examples. The approaches used tend to rely on adding chit-chat
snippets to pre-existing, human-generated task-oriented datasets. Given the
tendencies observed in humans, we wonder however if the latter do not
\textit{already} hold chit-chat sequences. By using topic modeling and
searching for topics which are most similar to a set of keywords related to
social talk, we explore the training sets of Schema-Guided Dialogues and
MultiWOZ. Our study shows that sequences related to social talk are indeed
naturally present, motivating further research on ways chitchat is combined
into task-oriented dialogues.
