Evolution of speech rhythm: a cross-species perspective
Bibliographic record
Abstract
Cognition and communication, at the core of human speech rhythm, do not leave a fossil record. However, if the purpose is to understand the origin and evolution of speech rhythm, alternative methods are available. A powerful tool is comparative approach: studying the presence or absence of cognitive/behavioral traits in other species, drawing conclusions on which traits are shared between species, and which are recent human inventions. Here we apply this approach to traits related to human speech rhythm. Many species exhibit temporal structure in their vocalizations but little is known about the range of rhythmic structures perceived and produced, their biological and developmental bases, and communicative functions. We review the literatures on human and non-human studies of rhythm in speech and animal vocalizations to survey similarities and differences. We report important links between vocal perception and motor coordination, and the differentiation of rhythm based on hierarchical temporal structure. We extend this review to quantitative techniques useful for computing rhythmic structure in acoustic sequences and hence facilitating cross-species research. While still far from a full comparative cross-species perspective of speech rhythm, we are closer to fitting missing pieces of the puzzle.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".