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Record W4377014227 · doi:10.1017/9781108604642.008

Voice, Phonation, and Nasality

2023· book-chapter· en· W4377014227 on OpenAlexaff

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLinguistics and Cultural Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhoneticsLinguisticsPhonationTerminologyComputer scienceAcoustic phoneticsSpeech productionNasalityPhonetic transcriptionVowelPhilosophy

Abstract

fetched live from OpenAlex

Phonetics is a fundamental building block not just in linguistics but also in fields such as communication disorders. However, introductions to phonetics can often assume a background in linguistics, whilst at the same time overlooking the clinical and scientific aspects of the field. This textbook fills this gap by providing a comprehensive yet accessible overview of phonetics that delves into the fundamental science underlying the production of speech. Written with beginners in mind, it focuses on the anatomy and physiology of speech, while at the same time explaining the very basics of phonetics, such as the phonemes of English, the International Phonetic Alphabet, and phonetic transcription systems. It presents the sounds of speech as elements of linguistic structure and as the result of complex biological mechanics. It explains complicated terminology in a clear, easy-to-understand way, and provides examples from a range of languages, from disorders of speech, and from language learning.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.008

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 head0.052
GPT teacher head0.197
Teacher spread0.144 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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