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Record W2765667893 · doi:10.5539/elt.v10n12p72

The Effects of L2 Experience and Vowel Context on the Perceptual Assimilation of English Fricatives by L2 Thai Learners

2017· article· en· W2765667893 on OpenAlexvenueno aff
Patchanok Kitikanan

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsnot available
FundersNaresuan University
KeywordsVowelPsychologyPerceptionContext (archaeology)LinguisticsMid vowelContext effectSpeech perceptionPhoneticsFormantGeographyWord (group theory)

Abstract

fetched live from OpenAlex

The aim of this study is to investigate the effect of vowel context and language experience in the perceived similarity between L2 English fricatives and Thai sounds. The target English sounds being investigated were the sounds /v, f, w, θ, tʰ, s, ð, d, z, ʃ, t͡ʃ/. These sounds were elicited from four native English speakers in words in onset position and followed by three vowel contexts: high, low and back. Subjects were 54 Thai students divided into two groups: English-major and non-English-major. These Thai learners were asked to identify the sounds they heard with the Thai sounds that were closest in their perception. The findings showed that 1) all shared sounds were matched with the same L1 categories, suggesting that the existence of L2 sounds in the L1 sound system supports the perception; 2) most non-shared sounds, except English /θ/ were matched to Thai sounds that were suggested in previous literature; 3) the perceived similarity of English /θ/ and the L1 Thai sounds showed the effect of the vowel context in that this sound was mostly matched with Thai /f/ in the high and low vowel contexts whereas in the back vowel context, it was matched with Thai /s/; 4) the perceived similarities of both shared and non-shared sounds were affected by vowel context and language experience. The findings of this study shed light on the importance exploring perceived similarities and differences in the phonetic level rather than the phonological one.

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.

How this classification was reachedexpand

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.333
Teacher spread0.317 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2017
Admission routes1
Has abstractyes

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