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Record W4411178604 · doi:10.1075/jslp.24031.gro

Production of American English consonants /v/ and /w/ by Hindi speakers of English

2025· article· en· W4411178604 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
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHindiLinguisticsAmerican EnglishHistoryProduction (economics)PsychologyPhilosophyEconomics

Abstract

fetched live from OpenAlex

Abstract Previous research revealed that Hindi speakers identify American English (AE) phonemes /v/ and /w/ with only chance accuracy. Building on these findings, this study explored the production of AE /v/ and /w/ by Hindi speakers, utilizing both acoustic analysis of second formant (F2) onset and AE listeners’ ratings. Participants included two groups of Hindi-English bilinguals, one residing in the US for more than 5 years, one residing in India, and a group of monolingual AE speakers. Results indicated significant differences in F2 onset between AE speakers and Hindi groups, with AE speakers differentiating the consonants more than the Hindi speakers did. The F2 onset of the Hindi speakers who had resided in the US differed from the F2 onsets produced by those with no AE immersion experience in certain conditions only. AE listeners rated only a few productions from Hindi speakers as accurate representations of AE /v/ and /w/. AE /v/-/w/ is difficult for Hindi speakers to produce contrastively, even for those who have resided in the US for several years.

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)0.001
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 score0.626
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.008
GPT teacher head0.300
Teacher spread0.292 · 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