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Speech rhythm and timing of a speech-impaired speaker

2012· article· en· W4390912743 on OpenAlexafffund
Tae-Jin Yoon, Karin R. Humphreys

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStress (linguistics)RhythmSpeech recognitionStress (linguistics)Speech productionSpeech processingComputer sciencePsychologyAudiologyLinguisticsMedicine

Abstract

fetched live from OpenAlex

We made quantitative rhythmic and timing measurements on speech samples obtained a 61 year-old monolingual female English speaker who is reported to have required a rare but possible case of Foreign Accent Syndrome (FAS). The phonetic characteristics of speech produced by individuals with FAS affects both suprasegmental and segmental properties. We used a large scale of speech samples to overcome difficulties of comparison due to the lack of speech samples before the accident. The results showed that the speaker has greater variability than control speakers, and that speech rate is slower, but that the rhythmic patterns were more to the stress timed. The results imply that the greater variability of the rhythmic and timing patterns in the speech-impaired speaker can be used as a means of identifying areas of speech production in the speech-impaired speaker.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.034
GPT teacher head0.290
Teacher spread0.257 · 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.

Study designObservational
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
Published2012
Admission routes2
Has abstractyes

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