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Record W2897846732 · doi:10.1121/1.5068107

Prosody as a window into speaker attitudes and interpersonal stance

2018· article· en· W2897846732 on OpenAlexaff
Marc D. Pell, Nikos Vergis, Jonathan A. Caballero, Maël Mauchand, Xiaoming Jiang

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsMcGill University
Fundersnot available
KeywordsProsodyPsychologyInterpersonal communicationEmotiveCovertPerceptionEmotional prosodyContext (archaeology)Cognitive psychologyLinguisticsSocial psychology

Abstract

fetched live from OpenAlex

New research is exploring ways that prosody fulfils different social-pragmatic functions in spoken language by revealing the mental or affective state of the speaker, thereby contributing to an understanding of speaker’s meaning. Prosody is often pivotal in signaling speaker attitudes or stance in the interpersonal context of the speaker-hearer; in contrast to the vocal communication of emotions, the significance of prosodic cues serving an emotive or interpersonal function is often dependent on the type of speech act being made and other contextual-situational parameters. Here, we discuss recent acoustic-perceptual studies in our lab demonstrating how prosody marks the interpersonal stance of a speaker and how this information is used by listeners to uncover social intentions that may be non-literal or covert. Focusing on how prosody operates in the communication of politeness, ironic attitudes, and sincerity, our data add to research on the acoustic-perceptual characteristics of prosody in these interpersonal contexts. Future implications for how acoustic cues underlying “prosodic attitudes” affect the interpretive process during on-line speech processing and how they influence behavioral outcomes are considered.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.999

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 studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.292
Teacher spread0.272 · 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 designQualitative
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

Citations3
Published2018
Admission routes1
Has abstractyes

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