MétaCan
Menu
Back to cohort
Record W3071414256 · doi:10.1017/s1360674320000222

Variable assimilation of English word-final /n/: electropalatographic evidence

2020· article· en· W3071414256 on OpenAlexaffabout
Alexei Kochetov, Laura Colantoni, Jeffrey Steele

Bibliographic record

VenueEnglish Language and Linguistics · 2020
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAssimilation (phonology)LinguisticsVariation (astronomy)PhonologyCategorical variableRealization (probability)Variable (mathematics)Range (aeronautics)PsychologyComputer scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

The phonetic realization of the English word-final alveolar nasal /n/ is known to be highly variable. Previous articulatory work has reported both gradient and categorical nasal place assimilation including considerable between-speaker differences. This work, however, has largely focused on a small subset of place contexts (namely, preceding velar /k, ɡ/) in a limited number of English varieties. The present article uses electropalatography to study the articulatory realization of /n/ in a wider range of phonetic contexts and read texts as produced by three speakers of Canadian English. The results reveal considerable inter- and intra-speaker differences in the rates of assimilation. Consistent with previous work, we observed a high degree of variation, both gradient and categorical, before velars. Substantial rates of assimilation were also observed before labials, where the process is unexpected from the point of view of gestural phonology but predicted by traditional phonological analyses. The variation in the place and stricture of /n/ before coronals was more limited and typically gradient. Finally, some differences were observed across the text conditions, with more assimilation occurring in carrier sentences than in the read passage and, to a more limited extent, in function than in content words.

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)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.015
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)0.0010.000

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 head0.043
GPT teacher head0.323
Teacher spread0.281 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueEnglish Language and LinguisticsSame topicPhonetics and Phonology ResearchFrench-language works237,207