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Record W4402988558 · doi:10.1177/13621688241282259

High variability phonetic training facilitates categorical perception of Mandarin lexical tones in L2 older adults: A link to auditory processing

2024· article· en· W4402988558 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 Teaching Research · 2024
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMcMaster UniversityCarleton University
Fundersnot available
KeywordsMandarin ChinesePsychologyPerceptionCategorical variableSpeech perceptionCognitive psychologyCategorical perceptionLinguisticsAudiologyComputer science

Abstract

fetched live from OpenAlex

The current study investigated the facilitatory effects of High Variability Phonetic Training (HVPT) in second language (L2) categorical perception (CP) of Mandarin lexical tones. It also explored whether and how individual differences in auditory processing predicted gains from such training. The participants were 32 native English-speaking adults aged over 60 years who were learning Mandarin Chinese as their L2. They were randomly divided into the HVPT group (HG) ( n = 16) and the control group (CG) ( n = 16). Their L2 CP performance was assessed through an identification task and discrimination task before training, immediately after training, and two months later. Auditory processing tests were also conducted to measure the participants’ ability to encode spectral and temporal details of sounds. Linear mixed-effects (LME) models showed that, compared to the CG, the HG exhibited a more pronounced improvement in tonal categorization. Furthermore, regression analysis confirmed that individual differences in perceptual acuity significantly predicted gains from training in L2 CP of Mandarin lexical tones.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.049
GPT teacher head0.431
Teacher spread0.382 · 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