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Record W4396666081 · doi:10.61989/00tnjs80

Le voyage d’Alice : un texte standardisé pour l’évaluation de la parole et de la voix en Français.

2023· article· en· W4396666081 on OpenAlexaffabout
Timothy Pommée, Liziane Bouvier, Julien Pinquier, Julie Mauclair, Véronique Delvaux, Cécile Fougeron, Corine Astésano, Vincent Martel‐Sauvageau, Dominique Morsomme, Pierre Pinçon, Muriel Lalain, Virginie Woisard

Bibliographic record

VenueGlossa. · 2023
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversité LavalMcGill UniversitySunnybrook HospitalSunnybrook Health Science CentreToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsReading (process)FluencyAlice (programming language)Protocol (science)Set (abstract data type)Computer scienceUSableSingingSpeech recognitionLinguisticsNatural language processingPsychologyMultimediaMathematics educationMedicine

Abstract

fetched live from OpenAlex

Background: Reading passages allow the observation of target stimuli in a controlled manner while maximizing the ecological aspects of a speech and voice assessment. Objective: This article presents a new standardized reading passage titled “Le voyage d’Alice” (“Alice's Journey”) and an automated protocol for the extraction of acoustic measures. Methods: The passage was constructed using a comprehensive set of criteria, taking into account data from the literature, specific needs identified in scientific research and in French-speaking clinical practice, and data from an international consensus study. Results: This passage was found to be easy to read and usable for the assessment of articulation of speech sounds, prosodic variations and phonatory behavior, as well as fluency, in Belgium, France, and Canada. The automated acoustic feature extraction protocol allows for a quick and simple analysis of reproducible data. It is a tool adapted for both scientific research and daily clinical practice. Acoustic measures were extracted from the passage in healthy participants in France and are used as reference values.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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)0.0010.002

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 head0.018
GPT teacher head0.387
Teacher spread0.369 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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