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Record W4410315950 · doi:10.1075/jslp.24057.lu

Linguistic dimensions of comprehensibility and perceived fluency in L2 speech across tasks of varying complexity

2025· article· en· W4410315950 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

VenueJournal of Second Language Pronunciation · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFluencyLinguisticsPsychologyCognitive psychologySpeech perceptionLinguistic sequence complexitySpeech recognitionComputer sciencePerception

Abstract

fetched live from OpenAlex

Abstract This study investigated the effects of task complexity on the linguistic dimensions of comprehensibility and perceived fluency in L2 Japanese. 36 Chinese-speaking learners of Japanese performed two argumentative speech tasks with differing levels of complexity. These audio samples were judged by eight experienced native raters of Japanese for comprehensibility and perceived fluency and then analyzed in terms of complexity, accuracy, and fluency. The results showed that linguistic correlates of comprehensibility exhibit a task-specific effect, with additional linguistic dimensions (e.g., syntactic density, explicit grammatical marking) becoming increasingly relevant as task complexity rises. In contrast, perceived fluency also undergoes a task-specific shift but differently: rather than expanding the set of predictors, it changes the nature of primary cues, placing greater emphasis on syntactic sophistication alongside (but not replacing) temporal aspects. Findings underscore the unique role of Japanese linguistic system in shaping listeners’ judgments of L2 Japanese.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.035
GPT teacher head0.334
Teacher spread0.299 · 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