Bibliographic record
Abstract
i n t r o d u c t i o nAt first glance, two phonemes such as /r/ and /d/ do not seem likely candidates to share a great deal of phonetic similarity.In near-natural speech where articulatory reduction is expected, though, /d/ realized as [ □ ] (a flap/tap) is commonplace in a number of languages including Japanese.Japanese /r/, or more properly / □ / , is largely considered to be an alveolar or post-alveolar tap subject to a wide degree of phonetic variability (e.g.Vance 1987;Akamatsu 1997) .Alongside canonical [ □ ] realizations, variants of /r/ in Japanese can include the lateral flap [ □ ] , lateral-and rhotic approximants [ □ , l] (Okada 1999; Amanuma et al. 2004) as well as what Hattori (1951) calls a 'weak [d]' ( or 'weak plosive' in Kawakami 1977; see also Vance , 1987).The weak plosive variant o f /r/ is generally discussed as a positional variant, occurring word-initially or following a pause.This author's earlier auditory-phonetic work with a corpus o f extemporaneous (Kansai) Japanese dialogue suggested (Magnuson 2008) that variation may also in part be individual.That is, in one conversational dyad each speaker's pattern of phonetic realization of /r/ differed widely.One speaker ('JFB') produced taps which included transients akin to the release bursts o f stops (i.e., 'weak plosives'), while the other speaker ('JFA') produced a number of these alongside a variety of taps as well as lateral-and rhotic approximants.This paper acoustically re-examines the same dataset to explore the hypothesis that the speaker who produced more plosive-like /r/s (JFB) would lengthen her phonetic realizations o f /d/ so as to avoid neutralizing her /r, d/ contrast.The conclusion arrived at is that this speaker does use duration to augment the contrast, but she does so by reducing the length of /r/ as opposed to lengthening /d/.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".