Principal component analysis of the interaction between spectral band power and pitch in classical singing voices

This study explores how the spectral information of vowel production targets changes by pitch in classical singing. Although it is established that singers engage in pitch-dependent vocal tract adjustments, less is known about how spectral envelope contrasts between vowel targets change by pitch and how consistent the patterns are across singers. Seven professional classical singers sang seven vowels across their pitch range. The energy of 16 spectral bands at every 500 Hz interval up to 8000 Hz was measured. Principal component analyses were performed to describe spectral variation. Results show consistent changes in spectral energy distribution as pitch increases despite individual differences in pitch range. A separate set of analyses further uses the center of gravity, standard deviation, skewness, and kurtosis of the spectra as a proxy for spectral shape variation, showing that the summarized spectral envelopes of vowel production targets systematically converge at higher pitches. Overall results suggest that pitch-dependent vocal tract adjustments may be shaped not only by singers' acoustic targets, but also by physiological constraints relative to each singer's overall pitch range. More broadly, this study demonstrates the possibility of using dimensionality reduction methods to characterize spectral patterns in high-pitched singing when formant tracking fails.

Authors

Institutions

Publication Details

Journal
The Journal of the Acoustical Society of America
Published
2025-12-01
DOI
https://doi.org/10.1121/10.0041780
Primary Topic
Phonetics and Phonology Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Principal component analysis of the interaction between spectral band power and pitch in classical singing voices

Jianjing Kuang, May Pik Yu Chan
The Journal of the Acoustical Society of America
Phonetics and Phonology Research
article

Principal component analysis of the interaction between spectral band power and pitch in classical singing voices

Jianjing Kuang, May Pik Yu Chan
article en

Abstract

This study explores how the spectral information of vowel production targets changes by pitch in classical singing. Although it is established that singers engage in pitch-dependent vocal tract adjustments, less is known about how spectral envelope contrasts between vowel targets change by pitch and how consistent the patterns are across singers. Seven professional classical singers sang seven vowels across their pitch range. The energy of 16 spectral bands at every 500 Hz interval up to 8000 Hz was measured. Principal component analyses were performed to describe spectral variation. Results show consistent changes in spectral energy distribution as pitch increases despite individual differences in pitch range. A separate set of analyses further uses the center of gravity, standard deviation, skewness, and kurtosis of the spectra as a proxy for spectral shape variation, showing that the summarized spectral envelopes of vowel production targets systematically converge at higher pitches. Overall results suggest that pitch-dependent vocal tract adjustments may be shaped not only by singers' acoustic targets, but also by physiological constraints relative to each singer's overall pitch range. More broadly, this study demonstrates the possibility of using dimensionality reduction methods to characterize spectral patterns in high-pitched singing when formant tracking fails.

The Journal of the Acoustical Society of AmericaVol. 158(6)
University of Pennsylvania (US)
Openalex Percentile: Top 59%
Phonetics and Phonology Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.