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Record W4231723620 · doi:10.1121/2.0000027

Phonetic Shifting Across Narrative and Quoted Speech Styles

2014· article· en· W4231723620 on OpenAlexaff
Paul De Decker

Bibliographic record

VenueProceedings of meetings on acoustics · 2014
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVowelNarrativeLinguisticsFormantStyle (visual arts)Duration (music)Performative utterancePsychologySpeech recognitionComputer scienceArtLiteraturePhilosophy

Abstract

fetched live from OpenAlex

Qualitative descriptions of speech accompanying verbs of quotation (e.g. "She was like, 'I'm not going in there!'") characterize quoted speech as a mimetic performance (Buchstaller 2003, Winter 2002) with "selective depictions" of the quotees words (Clark and Gerrig 1990, 1). The current study aims to quantify the performative and mimetic nature of quoted speech by comparing acoustic measurements of 539 vowel productions obtained through narratives of personal experience (Labov and Waletzky 1967) as told between friends. First and second formant frequencies were measured at the temporal midpoint of each vowel using PRAAT5.3 (Boersma and Weenink 2012), and compared using MANOVA tests in R. The dependent variables were F0, F1, F2, and duration while condition (quoted or non-quoted) served as the independent variable. Results indicate that mainly female speakers showed phonetically shifted vowel quality features when moving from narrative style speech to quoting voices for characters in their stories.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.328
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2014
Admission routes1
Has abstractyes

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