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%.

中文翻译：

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用于改进歌曲搜索的多模态合唱识别

我们讨论了一个新颖的任务，合唱识别，它可能有利于下游任务，如歌曲搜索和音乐摘要。与现有的依赖单模态信息的音乐摘要或歌词摘要等任务不同，本文利用歌曲的歌词和曲调信息将合唱识别建模为多模态识别。我们提出了一种考虑多种特征的多模态合唱识别模型。此外，我们还创建并发布了第一个合唱识别数据集，其中包含 627 首歌曲供公众使用。我们对数据集进行的实证研究表明，我们的方法在合唱识别方面优于几个基线。此外，我们的方法还有助于将其下游任务——歌曲搜索的准确率提高 10.6% 以上。