Problem
Research questions and friction points this paper is trying to address.
vocal music
phoneme-conditional analysis
acoustic dimensions
language identification
Vocal Music under Phoneme-Conditional Analysis
🤖 AI Summary
研究通过引入音素条件分析法，测量不同语言无伴奏声乐中特定音素的声学效应，从而识别歌曲的语言身份。
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
phoneme-conditional analysis
acoustic effect
marker syllables
unaccompanied vocal
language classification
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