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Record W2169270654 · doi:10.7575/aiac.alls.v.4n.1p.68

Prosodic Transfer: From Chinese Lexical tone to English Pitch Accent

2013· article· en· W2169270654 on OpenAlexaff
Marie Ploquin

Bibliographic record

VenueAdvances in Language and Literary Studies · 2013
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPitch accentTone (literature)LinguisticsProsodyPsychologyStress (linguistics)Pitch contourSyllableSpeech recognitionComputer science

Abstract

fetched live from OpenAlex

Chinese tones are associated with a syllable to convey meaning, English pitch accents are prominence markers associated with stressed syllables. As both are created by pitch modulation, their pitch contours can be quite similar. The experiment reported here examines whether native speakers of Chinese produce, when speaking English, the Chinese tone whose phonetic contour most closely matches the contour of the intended English pitch accent. Six native speakers of Chinese recorded English and Chinese sentences, all including the segment [fan]. Results show that the subjects produced a Chinese tone 2 where a rising pitch accents was required and thus that speakers of Chinese rely on their lexical tones inventory to produce English prosody. The results obtained with falling pitch accents are much less conclusive partly because of the difficulty in measuring tone 3 due to the high level of creak that accompanies it.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score0.769

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.393
Teacher spread0.379 · 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.

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

Citations6
Published2013
Admission routes1
Has abstractyes

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