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Record W1977413534 · doi:10.1121/1.4788442

The tube resonance model speech synthesizer

2005· article· en· W1977413534 on OpenAlexaff
Leonard C. Manzara

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2005
Typearticle
Languageen
FieldComputer Science
TopicSpeech Recognition and Synthesis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAcousticsRADIUSResonance (particle physics)Vocal tractPhysicsTube (container)Acoustic resonanceScatteringRange (aeronautics)OpticsMaterials scienceComputer scienceAtomic physics

Abstract

fetched live from OpenAlex

The Tube Resonance Model (TRM) synthesizer is an articulatory speech synthesizer implemented in software. It directly emulates the resonant behavior of the oropharyngeal and nasal tracts using digital waveguides. The oropharyngeal cavity is subdivided into 8 regions of unequal length, where particular regions correspond to the human articulators of tongue, teeth, and mouth. The radius (cross-sectional area) of each region can be varied independently over time. The differences in radii between regions gives rise to differences in acoustic impedance, which is modeled using two-way scattering junctions. The nasal cavity is composed of 5 equal-length sections, and is connected to the vocal tract via another section (the velum) using a three-way scattering junction. The total length of the tube can be varied over a continuous range, allowing one to synthesize male, female, and juvenile voices.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.962
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.247
Teacher spread0.230 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2005
Admission routes1
Has abstractyes

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