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Record W1489411746

Analysis of a vowel database

2008· article· en· W1489411746 on OpenAlexaffvenue
Peter F. Assmann, Terrance M. Nearey, Sneha V. Bharadwaj

Bibliographic record

VenueCanadian acoustics · 2008
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFormantVowelGeometric meanSentenceSpeech recognitionMathematicsAcousticsComputer scienceStatisticsNatural language processingPhysics
DOInot available

Abstract

fetched live from OpenAlex

The perceptual effects of upward and downward scaling of the formats in combination with changes in geometric mean fundamental frequency was investigated. A database of recordings from adults and children from the Dallas, Texas region was collected. A systematic relationship between the geometric mean of the format frequencies across all of the vowels for a given speaker and the geometric mean fundamental frequency was found. Vowels were recorded in hVd words, both in isolation and in a carrier sentence. Recordings were carried out over a 2.5-year period at the University of Texas at Dallas. Each recorded token was produced following a screen prompt that displayed the orthographic representation of the hVd word or sentence, along with an audio example spoken by an adult female from the Dallas area. It was observed that the geometric mean increases linearly with the geometric mean of the formant frequencies when data for males and females are combined.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.011

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 head0.021
GPT teacher head0.228
Teacher spread0.207 · 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

Citations10
Published2008
Admission routes2
Has abstractyes

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