Speech markers of psychedelic-induced psychological change
Bibliographic record
Abstract
Abstract 5-MeO-DMT, a potent, short-acting psychedelic, induces profound shifts in cognition, affect, and self-awareness. Because language explicitly expresses these domains and voice implicitly conveys them, both may serve as potential ‘biomarkers’ of behavioural change. This study introduces a novel framework for analysing baseline language and vocal features, pre- to post-psychedelic changes, assessing their potential to predict subjective experiences and psychological outcomes. Daily voice journals from 29 participants were collected via ‘RetreatBot’ for two weeks before and after 5-MeO-DMT (1×12 mg). Transcripts were analysed using NLP (bag-of-words for vocabulary; transformer model for textual affect), and acoustic features (e.g., pitch, jitter, shimmer) were extracted to assess vocal dynamics. Following 5-MeO-DMT, speech markers revealed increased cognitive language, decreased social words, and altered voice quality (increased jitter/shimmer). Baseline speech patterns predicted psychological preparedness, ego dissolution anxiety, emotional breakthrough, and post-experience well-being. This first longitudinal analysis of speech markers following psychedelic use demonstrates a shift from external focus to introspection. Speech markers predicted and tracked psychological transformation, establishing vocal journaling as a valuable framework for monitoring psychedelic-induced changes and facilitating integration.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".