From emotive voices to empathic brains: A neuropragmatic investigation of complaint processing
Bibliographic record
Abstract
Many of our social interactions prompt us to detect emotional signals produced by others, which are designed to project ourselves into their feelings and understand their affective state; in other words, to empathize. Complaining, for example, aims to engage the social affiliation of listeners by conveying a feeling of (social) pain. This feeling is best conveyed by paralinguistic signals such as speech prosody - the "tone of voice" - but may also depend on a number of contextual and socio-cultural factors. In the present thesis, I investigated how the brain processes emotive signals in complaining speech, how these processes relate to the notion of empathy, and how they are affected by markers of cultural identity such as speaker accent. Chapters 1 and 2 describe the creation, validation, and analysis of a large stimulus set comprising complaints and neutral speech from French and Québécois (French-Canadian) speakers. They reveal characteristic acoustic and perceptual patterns when speakers adopt a complaining strategy, enhancing the expressivity of complaints through the emotive use of prosody. Chapter 3 assesses how the brain initially processes emotive prosody, using event-related potentials (ERPs) from electroencephalography (EEG) measures. It suggests that listeners rapidly detect salient emotive signals in the voice, especially when speakers share the same cultural affiliation, whereas listeners must engage in increased processing efforts for out-group complaints. Chapter 4 shows that this early appraisal of prosody constrains the interpretation of complaints at later stages, such that with the proper tone of voice, one can complain about anything. Finally, Chapter 5 uses functional magnetic resonance imaging (fMRI) to identify brain networks involved in the empathic processing of complaints. It reveals that emotive (complaining) prosody engages regions associated with emotion perception, affective empathy, and mentalizing; meanwhile, accent-based group perception determines the empathic perspective of the listener, relying on sensorimotor resonance with in-group speakers and inferential processes with out-group speakers. Together, these chapters highlight the emotive role of vocal signals in complaints and social communication. Prosody operates as a reliable medium to convey feelings and elicit empathic processes, while speaker accent effects reveal how empathy is influenced by cultural constraints. Overall, this dissertation provides a unique neuroscientific perspective on everyday interpersonal communication, further elucidating mysteries of the emotional and social brain
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".