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Record W4245804456 · doi:10.1121/1.4801029

Acoustic characteristics of glottalized obstruents in Gitksan

2013· article· en· W4245804456 on OpenAlexaff
Michael David Schwan

Bibliographic record

VenueProceedings of meetings on acoustics · 2013
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsObstruentSalientSpeech recognitionComputer scienceFeature (linguistics)LinguisticsArtificial intelligenceVowel

Abstract

fetched live from OpenAlex

Glottalized obstruents are a defining feature in the phonetic inventory of languages of the Pacific Northwest. Gitksan (Tsimshianic), an endangered and understudied language in this region, is no exception. However, these segments, which have typically been labelled as ejectives by fieldworkers, have also been variously described as implosives or even as voiced ejectives. Evidently, the ability of fieldworkers to perceive these segments has proven difficult, even by those who have worked on the language for many years. This project seeks to describe some of the salient acoustic cues associated with glottalized obstruents in Gitksan by comparing glottalized and plain stops. While previous work has examined these stops only in word-initial position, the present study compares stops across positions within the word and across stressed and non-stressed environments. Speech tokens were collected from three fluent native speakers of three dialects of Gitksan in order to describe the prominent acoustic cues which characterize glottalized obstruents in Gitksan.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.298
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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