Influence of emotional prosody, content, and repetition on memory recognition of speaker identity
Bibliographic record
Abstract
Recognising individuals through their voice requires listeners to form an invariant representation of the speaker’s identity, immune to episodic changes that may occur between encounters. We conducted two experiments to investigate to what extent within-speaker stimulus variability influences different behavioural indices of implicit and explicit identity recognition memory, using short sentences with semantically neutral content. In Experiment 1, we assessed how speaker recognition was affected by changes in prosody (fearful to neutral, and vice versa in a between-group design) and speech content. Results revealed that, regardless of encoding prosody, changes in prosody, independent of content, or changes in content, when prosody was kept unchanged, led to a reduced accuracy in explicit voice recognition. In contrast, both groups exhibited the same pattern of response times (RTs) for correctly recognised speakers: faster responses to fearful than neutral stimuli, and a facilitating effect for same-content stimuli only for neutral sentences. In Experiment 2, we investigated whether an invariant representation of a speaker’s identity benefitted from exposure to different exemplars varying in emotional prosody (fearful and happy) and content ( Multi condition), compared to repeated presentations of a single sentence ( Uni condition). We found a significant repetition priming effect (i.e., reduced RTs over repetitions of the same voice identity) only for speakers in the Uni condition during encoding, but faster RTs when correctly recognising old speakers from the Multi, compared to the Uni, condition. Overall, our findings confirm that changes in emotional prosody and/or speech content can affect listeners’ implicit and explicit recognition of newly familiarised speakers.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".