Facial expressions alter the fundamental sound properties of speech
Bibliographic record
Abstract
Literature from across academic disciplines has demonstrated significant links between emotional valence and language. For example, Whissell’s Dictionary of Affect in Language defines three dimensions upon which the emotionality of words is describable, and Ekman’s Theories of Emotion include the perception and internalization of facial expressions. The present study seeks to expand upon these works by exploring whether holding facial expressions alters the fundamental speech properties of spoken language. Nineteen (19) participants were seated in a soundproof chamber and were asked to speak a series of pseudowords containing target phonemes. The participants spoke the pseudowords either holding no facial expression, smiling, or frowning, and the utterances recorded using a high-definition microphone and phonologically analysed using PRAAT analysis software. Analyses revealed a pervasive gender differences in frequency variables, where males showed lower fundamental but higher formant frequencies compared to females. Significant main effects were found within the fundamental and formant frequencies, but no effects were discerned for the intensity variable. While intricate, these results are indicative of an interaction between the activity of facial musculature when reflecting emotional valence and the sound properties of speech uttered simultaneously.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".