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Record W4392387455 · doi:10.3390/languages9030087

The Effect of Pitch Accent on the Perception of English Lexical Stress: Evidence from English and Mandarin Chinese Listeners

2024· article· en· W4392387455 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.

Bibliographic record

VenueLanguages · 2024
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsVowelMandarin ChineseStress (linguistics)SentenceSpeech recognitionStress (linguistics)LinguisticsWord (group theory)PsychologyPerceptionPitch accentVowel lengthComputer scienceNatural language processingProsody

Abstract

fetched live from OpenAlex

The relative weighting of f0 and vowel reduction in English spoken word recognition at the sentence level were investigated in one two-alternative forced-choice word identification experiment. In the experiment, an H* pitch-accented or a deaccented word fragment (e.g., AR- in the word archive) was presented at the end of a carrier sentence for identification. The results of the experiment revealed differences in the cue weighting of English lexical stress perception between native and non-native listeners. For native English listeners, vowel quality was a more prominent cue than f0, while native Mandarin Chinese listeners employed both vowel quality and f0 in a comparable fashion. These results suggested that (a) vowel reduction is superior to f0 in signaling initial stress in the words and (b) f0 facilitates the recognition of word initial stress, which is modulated by first language.

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)0.001
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 score0.646
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.015
GPT teacher head0.358
Teacher spread0.343 · 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