SLPOtherJournal of voice : official journal of the Voice Foundation2026

A Chaotic Approach to Glottal Gap Voice.

Katerina A Smereka, Colbey Johnson, Alexa Q Guastello and 3 others

PMID 38886137

WHAT IT FOUND

In excised dog larynges, larger glottal gaps increased signal irregularity (D2) but only markedly worsened acoustic quality (CPP) at the widest gap tested.

Harmonics-to-noise ratio failed to track gap size reliably. This is an ex-vivo mechanical study, not clinical evidence.

Key findings

01Correlation dimension (D2) increased significantly with larger glottal gaps, indicating more irregular, chaotic voice signals.

02Cepstral peak prominence (CPP) showed a weak negative correlation with gap size, but significant drops in acoustic quality occurred only at the 0 mm vs shim comparison and the 3.5 mm threshold.

03Harmonics-to-noise ratio (HNR) did not show a clear relationship with glottal gap size and was not a reliable predictor of aperiodicity in this model.

STILL TO COME

How it was doneWhat they foundWhat it means for SLPs

Read the rest of this summary

You get three full summaries a month, free, and we do not ask for a card. Search, the TL;DRs and your library stay unlimited either way.

Already have one?

What it does not show

The study used excised canine larynges, which lack the neuromuscular control, tissue properties, and compensatory mechanisms of living human voices. Vocal fold tension and adductive force were not measured or controlled, which are critical factors in real-world voice production. The sample size was small (n=8), and the study was purely mechanical without patient outcomes or perceptual ratings. The authors explicitly state these methods are not to be used in isolation for diagnostic purposes.

Declared interests

None declared.

The easy way to misread this

Do not apply these acoustic thresholds to human patients. The study used dead dog larynges without muscle control, so the specific gap sizes and metric changes do not translate to clinical voice disorders.

Summarised by AI from the full paper, without a clinician reviewing it. Check it against the source before it changes what you do. Read it on PubMed →