Word frequency, predictability, and lexical class influence different aspects of Spanish tonic vowel production
Bibliographic record
Abstract
The influence of lexical factors on speech production has not yet been investigated in Spanish to the same extent as for other languages such as English, French, Dutch, and German. Addressing this literature gap, the present study investigates how word frequency, predictability, and lexical class affect the duration and first two formant values of tonic monophthong vowels (hereafter vowels) produced by monolingual Spanish speakers from Madrid using the Nijmegen Corpus of Casual Spanish [Torreira and Ernestus, LREC'10 (2010), pp. 2981–2985]. A tonic vowel is defined as the most prominent vowel in a word's citation form. Word frequency and predictability based on the preceding word were calculated using the Spanish data from the OpenSubtitle corpus [Lison and Tiedemann, LREC'16 (2016), pp. 923–929]. Results of statistical modelling showed that the three aspects of vowel production under study were affected by all the examined lexical characteristics, although the effect sizes were small. Results are discussed in the context of previous work on Spanish vowels and cross-linguistic trends in speech production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".