ArtiSynth designing a modular 3D articulatory speech synthesizer
Bibliographic record
Abstract
ArtiSynth is a modular, component-based system for performing dynamic 3D simulations of the human vocal tract and face. It provides a test bed for research in areas such as speech synthesis, linguistics, medicine, and dentistry. ArtiSynths framework enables researchers to construct, refine, and exchange models of all parts of the vocal tract and surrounding structures. ArtiSynth introduces a probe concept to unify input and output data flow, which allows control of and access to models with time varying data series. ArtiSynth supports interconnected heterogeneous models, such as rigid body, mass-spring, and parametric, using a point-set connection method, called markers, for constraint satisfaction. Using ArtiSynth, we created a muscle-driven rigid body jaw model, a parametric principle component tongue model from MRI images, a parametric lip model, and mass-spring face tissue model. We combined them in various ways. Data from medical imaging (MRI, CT, and ultrasound) and other technologies such as optical tracking can be used to drive ArtiSynth models. We are currently developing an acoustical rendering framework supporting source-filter models and other advanced methods. The system incorporates a powerful scripting interface as well as an easy-to-use graphical interface. [Work supported by NSERC Canada and ATR Japan.]
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".