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Record W3126541686 · doi:10.22158/sll.v5n1p46

Phonology and Phonetics of L2 Telugu English

2021· article· en· W3126541686 on OpenAlexaff
Katerina Pisegna, Veno Volenec

Bibliographic record

VenueStudies in Linguistics and Literature · 2021
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsConcordia UniversityMcGill University
Fundersnot available
KeywordsObstruentLinguisticsTeluguVowelPhonologyPhoneticsContext (archaeology)MathematicsComputer scienceHistoryPhilosophy

Abstract

fetched live from OpenAlex

The paper provides a partial phonological and phonetic description of the segmental structure of L2 Telugu English (TE). Previous research on the subject has been carried out in the context of a more general notion of Indian English (IE), so the properties of TE as distinct from other varieties of IE (e.g., Gujarati English) have largely remained unexplored. We have primarily focused on areas that previous research identified as prominent issues in the study of IE: vowel inventory and production, representation and realization of liquids, word-final obstruent phenomena, and allophones of /w/. To account for these aspects of TE, we have combined a generative approach to the study of an individual’s linguistic competence with linguistic fieldwork as a means of collecting first-hand data. On the basis of collected data, we have conducted a spectrographic analysis of TE vowels and a distributional analysis of TE consonants. The paper provides the first description of the acoustic spaces of TE vowels. We found that all vowels except [?] and [i] are more central in TE than in General American English. /r/ was realized as either [r] or [?] without a specific pattern, and occasionally as [?] in the intervocalic position. /l/ was realized as [?] in word-final position and as [l] elsewhere. TE displayed word-final obstruent devoicing for all obstruents except for /b/, which was consistently unreleased. /w/ was realized as [?] before front vowels and as [w] elsewhere. While previous research that concentrated on the broad notion of Indian English recognized the issue of /w/-allophony, it has not provided a principle that governs the exact distribution of /w/’s allophones. By combining the generative framework with linguistic fieldwork, we have accounted for this long-standing puzzle with a single rule: /w/ ? [?] / __ [–CONS, –BACK].

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.044
GPT teacher head0.398
Teacher spread0.355 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2021
Admission routes1
Has abstractyes

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