A Focus on the Voice: Attention as a Unifying Mechanism Underlying Vocal Training and Mindfulness
Bibliographic record
Abstract
Recent decades have generated a proliferation of research into the phenomenon known as mindfulness. This literature gives voice and speech researchers an opportunity to reconceptualize and assess their practices. Voice and Speech Training (VST) for actors shares certain techniques and attitudes in common with mindfulness. Thus, it is plausible that these two practices rely on similar psychological and neurological mechanisms and may produce similar benefits. We provide an interdisciplinary review of the contemporary literature regarding vocal production, VST practices, mindfulness, and meditation, highlighting conceptual and practical connections between them. We propose that attention is a common mechanism that unifies VST practices and mindfulness. We provide an overview of how attention and mindfulness meditation have been conceptualized and summarize recent empirical studies on their possible relationship. Finally, we suggest future directions for how interdisciplinary research teams might investigate the relationship between VST, mindfulness, and attention, and bring empirical methodologies to bear on questions of artistic significance.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".