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Record W4413434737 · doi:10.1080/02699206.2025.2548213

Reduction of hypernasal speakers’ nasalance scores with voice focus adjustments: Replication and expansion of findings

2025· article· en· W4413434737 on OpenAlexafffund
Tim Bressmann, Loredana Cuglietta, Betty Tang, Charlene Santoni

Bibliographic record

VenueClinical Linguistics & Phonetics · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsStollery Children's HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsPsychologyFocus (optics)LinguisticsReplication (statistics)AudiologyMedicinePhilosophy

Abstract

fetched live from OpenAlex

Speech therapy exercises are not considered effective to reduce hypernasality in the speech of children with cleft palate. Previous research studies have shown that nasalance scores of hypernasal speakers were lower in backward and higher in forward voice focus. Conversely, some individual speakers had lower nasalance scores in forward voice focus. The present study sought to replicate and further expand these findings. The study investigated how many hypernasal speakers in a small convenience sample could lower their nasalance using voice focus. For 6 hypernasal speakers (4 F, 2 M, ages 5-18) with repaired cleft palate, nasalance scores were recorded for a non-nasal sentence, a nasal sentence, 2 phonetically varied sentences and a short song at baseline, in backward voice focus, in forward voice focus and at a final baseline. For individual speakers, reductions in nasalance of -10% from baseline were considered meaningful. Mean nasalance scores for all stimuli combined changed significantly from 58.2% nasalance (SD 11.3) at baseline to 44.2% (SD 15.3) in backward voice focus, 60.8% (SD 17.6) in forward voice focus, and 53.0% (SD 11.9) at the final baseline. Nasalance scores in the backward voice focus were significantly lower than the initial baseline and forward voice focus conditions. Inspection of individual scores showed that 4 of the 6 participants showed pronounced reductions in nasalance scores of up to -44% in backward and up to -23% in forward voice focus. Further research about the potential effectiveness of this approach for speech therapy should be undertaken.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.356
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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