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Record W4407058246 · doi:10.1177/00238309241311924

Prosodic Cues for Broad, Narrow, and Corrective Focus in Persian

2025· article· en· W4407058246 on OpenAlex
Mortaza Taheri-Ardali, Simon Roessig, Lena Pagel, Doris Mücke

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 · 2025
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsCarleton University
FundersUniversität zu KölnDeutsche Forschungsgemeinschaft
KeywordsFocus (optics)ProsodySyllableStress (linguistics)Perspective (graphical)UtterancePsychologyDuration (music)LinguisticsComputer scienceSpeech recognitionArtificial intelligenceAcoustics

Abstract

fetched live from OpenAlex

Previous studies have demonstrated that focus significantly alters sentential prosody in Persian. However, research on the phonetic realization of non-corrective narrow focus is scarce compared to that on broad and corrective focus. This paper presents a systematic production study investigating whether Persian speakers distinguish between three focus structures on target words that bear a pitch accent, that is, broad, narrow, and corrective focus. In a multidimensional phonetic analysis, we investigated the parameters of intensity, duration, and F0. Taking a local perspective, results show that the duration of the target word is a robust cue for focus marking in both syllables of the word, exhibiting a three-step pattern (corrective > narrow > broad). In the first syllable, intensity is a reliable cue to distinguish broad focus from the other two focus types, with higher intensities in broad focus. In the accented syllable, a different two-step pattern is observed, with narrow and corrective focus showing larger F0 spans than broad focus. Taking a global perspective that considers the parts of the utterance before and after the target word, we find a lowering of F0 and decreased intensity for narrow and corrective focus in the pre-target region. In the post-target region, we find strong evidence for differences in mean F0 and intensity with lower F0 in corrective focus than in broad and narrow focus, while the intensity is lower in narrow and corrective focus than in broad focus. Our analysis deepens our understanding of Persian prosody.

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)0.000
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 score0.686
Threshold uncertainty score0.251

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)0.0000.000

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 head0.012
GPT teacher head0.346
Teacher spread0.334 · 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