  We discuss a novel task, Chorus Recognition, which could potentially benefit
downstream tasks such as song search and music summarization. Different from
the existing tasks such as music summarization or lyrics summarization relying
on single-modal information, this paper models chorus recognition as a
multi-modal one by utilizing both the lyrics and the tune information of songs.
We propose a multi-modal Chorus Recognition model that considers diverse
features. Besides, we also create and publish the first Chorus Recognition
dataset containing 627 songs for public use. Our empirical study performed on
the dataset demonstrates that our approach outperforms several baselines in
chorus recognition. In addition, our approach also helps to improve the
accuracy of its downstream task - song search by more than 10.6%.
