Minimal Perturbation-Based Segment Selection in Connected Speech Differentiates Healthy and Pathological Voice.
Owen P Wischhoff, Maiwand M Tarazi, Jakob R Holm and 3 others
PMID 42538221WHAT IT FOUND
A moving-window method applied to connected speech separated 41 healthy from 41 pathological voices across all three acoustic measure groups.
CPP showed the strongest separation. This suggests connected speech is a viable medium for acoustic voice assessment alongside sustained vowels.
Key findings
01All three acoustic measure groups (nonlinear dynamic, perturbation, and spectral) showed significant healthy-versus-pathological differences that survived within-group false discovery rate correction in connected speech.
02CPP produced the largest effect size of any measure in the study (d = 1.953), with pathological speakers showing markedly lower values than healthy speakers.
03The minimal perturbation method, previously validated in sustained vowel phonation, generalizes to connected speech and enables acoustic discrimination without controlled phonatory tasks.
STILL TO COME
How it was doneWhat they foundWhat it means for SLPs
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What it does not show
The pathological group is heterogeneous, spanning organic, neurological, and functional voice disorders, so the findings cannot be attributed to any single diagnosis. A direct comparison to sustained vowel recordings was not possible because the database cut disordered sustained samples at 1 second, limiting the ability to confirm whether connected speech adds value over the traditional task. Age and sex were not entered as covariates in the primary analysis, so a demographic contribution to the observed differences cannot be ruled out. The study compared only two discrete groups (healthy vs. pathological) and was not designed to determine whether any measure scales proportionally with dysphonia severity. Window parameters (0.8-second windows, 0.25-second shifts) were carried over from sustained-vowel work and have not been optimised for connected speech or for different passage types and speaker populations. All recordings used a single standardised passage (the Rainbow Passage), so generalisability to conversational speech or other texts is untested.
Declared interests
The authors declare no competing financial interests, no personal relationships that could have influenced the work, and no conflicts of interest. No funding source is named.
The easy way to misread this
Do not read the significant group differences as evidence that this method can diagnose an individual patient's voice disorder. The study reports between-group t-tests with 41 speakers per group; no sensitivity, specificity, or individual classification accuracy was reported, and the pathological group spans organic, neurological, and functional disorders, so a significant group difference does not tell you what to do for a specific patient in front of you.