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Record W1920148782 · doi:10.1109/icassp.1979.1170591

Speech synthesis from vocal tract area function acoustical measurements

2005· article· en· W1920148782 on OpenAlexaff
B. Tousignant, J.-P. Lefèvre, M. Lecours

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSpeech Recognition and Synthesis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsVocal tractFormantGlottisVowelSpeech synthesisInterpolation (computer graphics)AcousticsSpeech recognitionComputer scienceSpeech productionLarynxArtificial intelligencePhysicsAnatomyMedicineMotion (physics)

Abstract

fetched live from OpenAlex

This paper presents studies and experiments in vocal-tract area function acoustical measurements and in speech synthesis from a physiological model of the vocal tract and the vocal cords. Following previous work by the same authors, problems associated with dynamic measurements of the vocal tract, with the quantization and interpolation of area functions are discussed and area function measurements for fixed and moving vocal tracts configurations corresponding, to sustained vowels and vowel transitions are presented. Experimental results illustrate the determination of lips and glottis position, and of the vocal tract length. Comparisons have been made with available data for vocal tract shape and formant characteristics. Speech synthesized from measured area functions is demonstrated.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.067
GPT teacher head0.253
Teacher spread0.185 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreMethods

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
Published2005
Admission routes1
Has abstractyes

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