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Producing appropriate prosodic cues in a non-dominant language: preliminary results from French-English bilinguals

2017· article· en· W3006693682 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueExLing Conferences · 2017
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMontreal Neurological Institute and HospitalMcGill UniversityCentre for Research on Brain Language and Music
FundersCentre for Research on Brain, Language and Music
KeywordsProsodyStress (linguistics)Computer sciencePhraseSyllableLinguisticsPerceptionDuration (music)Natural language processingSpeech recognitionPsychology

Abstract

fetched live from OpenAlex

Adapting one’s production of prosodic cues to a second or non-dominant language can be difficult. The present study focuses on French-English bilinguals’ ability to adapt their prosody to coordinate phrase-final lengthening and lexical stress. Because French has no lexically-coded prosody, it might be difficult for French-dominant speakers to simultaneously control lexical and phrasal prosodic cues. Our preliminary results demonstrate that not only the speaker’s L1, but the relative dominance of one language over another can predict speakers’ ability to adapt prosody to the specific demands of different languages, at least with respect to controlling syllable duration. These findings are in line with recent results showing that native French listeners do not process lexical stress automatically, instead relying on alternative perceptual mechanisms.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0010.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.367
Teacher spread0.319 · 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