VivesDebate-Speech: A Corpus of Spoken Argumentation to Leverage Audio Features for Argument Mining
This addresses a data gap for researchers in speech processing and argument mining, but it is incremental as it builds on existing text-based argument mining methods.
The authors tackled the lack of spoken argumentation data by creating the VivesDebate-Speech corpus, and their experiments showed that integrating audio features improves argument mining performance, though no specific numbers are provided.
In this paper, we describe VivesDebate-Speech, a corpus of spoken argumentation created to leverage audio features for argument mining tasks. The creation of this corpus represents an important contribution to the intersection of speech processing and argument mining communities, and one of the most complete publicly available resources in this topic. Moreover, we have performed a set of first-of-their-kind experiments which show an improvement when integrating audio features into the argument mining pipeline. The provided results can be used as a baseline for future research.