# Vocal Music under Phoneme-Conditional Analysis

arXiv: https://arxiv.org/abs/2608.30823 · HTML: https://mlsanity.com/paper/2608.30823/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 55 references that are in the map.
- First posted on arXiv 31 Aug 2026.

## Builds on (most cited first, 5 of 5)

- [Scaling Speech Technology to 1,000+ Languages](https://mlsanity.com/paper/2305.13516/) (2023)
- [RMVPE: A Robust Model for Vocal Pitch Estimation in Polyphonic Music](https://mlsanity.com/paper/2306.15412/) (2023)
- [GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks](https://mlsanity.com/paper/2409.13832/) (2024)
- [Mel-RoFormer for Vocal Separation and Vocal Melody Transcription](https://mlsanity.com/paper/2409.04702/) (2024)
- [FCPE: A Fast Context-based Pitch Estimation Model](https://mlsanity.com/paper/2509.15140/) (2025)

## Abstract (arXiv)

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.