标题： 旋律-歌词匹配的对比对齐损失 显示英文标题

标题： Melody-Lyrics Matching with Contrastive Alignment Loss

摘要： 音乐与歌词之间的联系远超语义纽带。 两种模态中的概念对，如节奏与押韵、音符时长与音节重音以及结构对应关系，在音乐信息检索领域提出了一个引人注目但很少被探索的方向。 在本文中，我们提出了一种新的任务——旋律-歌词匹配（MLM），该任务从文本资源中检索给定符号旋律的潜在歌词。 与从头生成歌词不同，MLM本质上利用了旋律与歌词之间的关系。 我们提出了一种带有对比对齐损失的自监督表示学习框架，用于旋律和歌词。 这有望利用现有成对旋律和歌词的丰富数据。 不需要对齐标注。 此外，我们引入了sylphone，这是一种新颖的歌词音节级表示，由音素身份和元音重音激活。 我们通过实证结果和直观示例证明，我们的方法可以与连贯且可唱的歌词进行匹配。 我们开源了代码，并在配套网页上提供了匹配示例：https://github.com/changhongw/mlm。 显示英文摘要

摘要： The connection between music and lyrics is far beyond semantic bonds. Conceptual pairs in the two modalities such as rhythm and rhyme, note duration and syllabic stress, and structure correspondence, raise a compelling yet seldom-explored direction in the field of music information retrieval. In this paper, we present melody-lyrics matching (MLM), a new task which retrieves potential lyrics for a given symbolic melody from text sources. Rather than generating lyrics from scratch, MLM essentially exploits the relationships between melody and lyrics. We propose a self-supervised representation learning framework with contrastive alignment loss for melody and lyrics. This has the potential to leverage the abundance of existing songs with paired melody and lyrics. No alignment annotations are required. Additionally, we introduce sylphone, a novel representation for lyrics at syllable-level activated by phoneme identity and vowel stress. We demonstrate that our method can match melody with coherent and singable lyrics with empirical results and intuitive examples. We open source code and provide matching examples on the companion webpage: https://github.com/changhongw/mlm.