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Record W2049402014 · doi:10.1177/00238309070500030401

The Effect of Pitch Peak Alignment on Sentence Type Identification in Russian

2007· article· en· W2049402014 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

VenueLanguage and Speech · 2007
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInterrogativeSyllableIntonation (linguistics)SentencePerceptionSpeech recognitionPitch accentPsychologySyllabic verseInterrogative wordLinguisticsProsodyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This paper reports the results of an experimental phonetic study examining pitch peak alignment in production and perception of three-syllable one-word sentences with phonetic rising-falling pitch movement by speakers of Russian. The first part of the study (Experiment 1) utilizes 22 one-word three-syllable utterances read by five female speakers of Russian as a declarative, an exclamation, and an interrogative. Significant differences in the alignment of pitch peak across declaratives and exclamations on the one hand and interrogatives on the other hand are observed. The second experiment tests whether these pitch peak alignment differences are employed in speech perception. Experiment 2 is performed with a series of resynthesized three-syllable stimuli which differ by 14 locations of the pitch peak, two segmental bases used for resynthesis (declarative and interrogative) and two heights of the pitch peak (270 and 320Hz). The results of the experiment demonstrate that a shift in pitch peak alignment strongly affects listeners' perception of sentence type. The effects of pitch height and segmental base are also significant. Implications for Russian intonation system are discussed.

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)0.000
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 score0.716
Threshold uncertainty score0.127

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.011
GPT teacher head0.346
Teacher spread0.336 · 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