A large portion of society united around the same vision and ideas carries
enormous energy. That is precisely what political figures would like to
accumulate for their cause. With this goal in mind, they can sometimes resort
to distorting or hiding the truth, unintentionally or on purpose, which opens
the door for misinformation and disinformation. Tools for automatic detection
of check-worthy claims would be of great help to moderators of debates,
journalists, and fact-checking organizations. While previous work on detecting
check-worthy claims has focused on text, here we explore the utility of the
audio signal as an additional information source. We create a new multimodal
dataset (text and audio in English) containing 48 hours of speech. Our
evaluation results show that the audio modality together with text yields
improvements over text alone in the case of multiple speakers. Moreover, an
audio-only model could outperform a text-only one for a single speaker.Comment: check-worthy claims, fake news, political debates, audi