Modelo autosegmental y entonación:los corpus DIES-RTVP
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The pre-toneme (all pre-nuclear pitch accents generated by the concatenation of static levels H(igh) and L(ow) to segments) has been analyzed. Six materials of spontaneous speech (DIES-RTVP corpora) emitted by two male speakers (Bilbao and Córdoba, debates), by a male speaker and a female speaker (Madrid, broadcasting voices), and by two female speakers (Madrid, cultural journalists) have been acoustically examined. Pitch accents are classified according to micro-spaces determined by psycho-phonetic differences, the tonal threshold in each accent rules the opposition H versus L. Results indicate a high frequency of appearance of pitch accents (H* , L+ H* , (L+H*)+L) and a low frequency of appearance of pitch accents integrated by L*. These findings are similar to the obtained in Buenos Aires discourses and in Madrid discourses (CREA corpora). Results do not support the view that pre-nuclear pitch accents in Hispanic dialects are constant (an occurrence of L*+H due to overshooting) but the opposite, the presence of a complex taxonomy.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 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