Reordering: a stepping-stone to perfect Thai Sign generation
Why this work is in the frame
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Bibliographic record
Abstract
We proposed the Sign Code Reordering approach (SCR) for reordering the intermediate sign codes (ISC) to Sign code script (SCS) generation. SCR uses language structure matching techniques to reduce complicated grammar rules, provide efficient results. SCR comprises three steps: extraction, reordering and integration. The distinction between source and target language in both grammar and vocabulary is concerned in each processing step to ensure the accuracy of reordering. SCR focuses on accurate and acceptable reordering that are not conforming to the original structure. SCR was designed to capture linguistic differences such as phrase, sentence and multi-sentence structures, no matter how long the input sentence is. The SCR prototype system was implemented and tested to reorder a number ISCs. The test results have been proved that SCR arranges ISCs successfully. SCR can be augmented into any NLP application which requires ISC arrangement e.g., T3STS. T3STS translates Thai text into Thai Sign language. Thai Sign language is the language of the Deaf in Thailand.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it