面向民歌歌词跨文化研究的机器翻译方法
Towards cross-cultural study of folksong lyrics with machine translation
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- Charles University（查理大学）
- University of Music and Performing Arts Graz（格拉茨音乐与表演艺术大学）
- Graduate School of Culture Technology（文化技术研究生院）
- KAIST（韩国科学技术院）
- Utrecht University（乌得勒支大学）
- Institute of Ethnology（民族学研究所）
- Czech Academy of Sciences（捷克科学院）
- Estonian Literary Museum（爱沙尼亚文学博物馆）
- NAS of Ukraine（乌克兰国家科学院）
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中文总结 AI 辅助
本研究利用机器翻译和神经主题模型，分析五种语言的民歌歌词，探讨内容与社会功能的关系，揭示跨文化联系，为跨文化歌词分析提供初步方法。
中文摘要 AI 辅助
音乐普遍存在于人类社会中。民族音乐学家长期以来一直在记录人类音乐性的多样表达，而比较音乐学最近将几项民歌研究推向了更全球化的规模。这种跨文化研究尚未在歌词领域开展：语言障碍迄今阻碍了多语言数据的处理。然而，自然语言处理（NLP）技术已发展到语言障碍可能不再构成阻碍的阶段。我们结合五种语言的民歌歌词语料库，使用预训练的神经主题模型将其机器翻译为枢轴语言，并考察每种语言内部以及跨语言（针对婚礼歌曲）内容与社会功能之间的关系。正如预期，人工评估翻译结果显示，非印欧语言的整体翻译质量较差。主题模型实验随后表明，在所有语言中，歌词内容至多仅部分与民歌的社会功能相关。这些实验只是跨文化民间音乐歌词分析的初步步骤；然而，它们确实表明，通过研究世界各地多样化民间音乐中人们所唱的歌曲，可能揭示出超越民族音乐学类型学的、此前未被观察到的跨文化关系网络。
英文摘要
Music is universally present in human societies. Ethnomusicologists have long been documenting the diverse expressions of human musicality, and comparative musicology has recently brought several studies of folksong to a more global scale. Such cross-cultural research has not been conducted on lyrics: the language barrier has so far prevented work with multi-lingual data. However, Natural Language Processing (NLP) technologies have reached a stage where this language barrier may no longer be prohibitive. Combining folksong lyrics corpora across five languages, we machine-translate them to a pivot language with a pre-trained neural topic model, and we examine the relationship between content and social function within each language, and across languages for wedding songs. As expected, human evaluation of translation results shows that non-Indo-European languages suffer from overall worse translation quality. Experiments with topic models then indicate that the content of lyrics is at best partially related to the social function of folksongs across all languages. These experiments are just first steps into cross-cultural folk musics lyrics analysis; however, they do indicate that a previously unobserved web of cross-cultural relationships beyond ethnomusicological typologies may be uncovered through the study of what people sing across the world's diverse folk musics.
