音素条件分析下的声乐
Vocal Music under Phoneme-Conditional Analysis
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中文总结 AI 辅助
该研究提出音素条件分析方法，通过9种语言的数千首无伴奏歌曲实验，以85.5%的平衡准确率识别语言，发现音系结构在演唱中留下可测量痕迹。
中文摘要 AI 辅助
每种语言的声乐即便没有乐器伴奏，也带有独特的声学特征。我们探究这些差异是否可测量且可追溯至特定音素。为解决该问题，我们提出音素条件分析方法，该方法通过在同一首歌曲内将标记音节与匹配的非标记对照音节进行比较，同时保持歌手、旋律和体裁不变，从而分离出类型学上独特音素的声学效应。我们在9种类型学多样的语言和数千首歌曲中，沿5个声学维度测量效应。由这些效应构建的歌曲层面特征，在按艺术家分组的9类分类任务中，以85.5%的平衡准确率识别无伴奏声乐的语言；这种可分性是否源于音素局部效应本身的积累仍待探究。我们的发现表明，音系结构在每种语言的演唱方式中留下了系统且可测量的痕迹。
英文摘要
The vocal music of each language carries a distinctive sonic identity, even without instrumental accompaniment. We ask whether these differences are measurable and traceable to specific phonemes. To tackle this question, we introduce phoneme-conditional analysis, which isolates the acoustic effect of typologically distinctive phonemes by comparing marker syllables against matched non-marker controls within the same song, holding singer, melody, and genre constant. Across nine typologically diverse languages and thousands of songs, we measure effects along five acoustic dimensions. Song-level profiles built from these effects identify the language of an unaccompanied vocal at 85.5% balanced accuracy in a nine-way classification with folds grouped by artist; whether the separability arises by accumulation of the phoneme-local effects themselves is left open. Our findings suggest that phonological structure leaves systematic and measurable traces in how each language is sung.
