Norm-Based Coding of Voice Identity in Human Auditory Cortex
Why this work is in the frame
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Bibliographic record
Abstract
Listeners exploit small interindividual variations around a generic acoustical structure to discriminate and identify individuals from their voice—a key requirement for social interactions. The human brain contains temporal voice areas (TVA) [1Belin P. Zatorre R.J. Lafaille P. Ahad P. Pike B. Voice-selective areas in human auditory cortex.Nature. 2000; 403: 309-312Crossref PubMed Scopus (1314) Google Scholar] involved in an acoustic-based representation of voice identity [2Charest I. Pernet C. Latinus M. Crabbe F. Belin P. Cerebral Processing of Voice Gender Studied Using a Continuous Carryover fMRI Design.Cereb. Cortex. 2013; 23: 958-966Crossref PubMed Scopus (37) Google Scholar, 3Latinus M. Crabbe F. Belin P. Learning-induced changes in the cerebral processing of voice identity.Cereb. Cortex. 2011; 21: 2820-2828Crossref PubMed Scopus (55) Google Scholar, 4Andics A. McQueen J.M. Petersson K.M. Gál V. Rudas G. Vidnyánszky Z. Neural mechanisms for voice recognition.Neuroimage. 2010; 52: 1528-1540Crossref PubMed Scopus (119) Google Scholar, 5Formisano E. De Martino F. Bonte M. Goebel R. “Who” is saying “what”? Brain-based decoding of human voice and speech.Science. 2008; 322: 970-973Crossref PubMed Scopus (392) Google Scholar, 6von Kriegstein K. Eger E. Kleinschmidt A. Giraud A.L. Modulation of neural responses to speech by directing attention to voices or verbal content.Brain Res. Cogn. Brain Res. 2003; 17: 48-55Crossref PubMed Scopus (235) Google Scholar], but the underlying coding mechanisms remain unknown. Indirect evidence suggests that identity representation in these areas could rely on a norm-based coding mechanism [4Andics A. McQueen J.M. Petersson K.M. Gál V. Rudas G. Vidnyánszky Z. Neural mechanisms for voice recognition.Neuroimage. 2010; 52: 1528-1540Crossref PubMed Scopus (119) Google Scholar, 7Papcun G. Kreiman J. Davis A. Long-term memory for unfamiliar voices.J. Acoust. Soc. Am. 1989; 85: 913-925Crossref PubMed Scopus (74) Google Scholar, 8Bruckert L. Bestelmeyer P. Latinus M. Rouger J. Charest I. Rousselet G.A. Kawahara H. Belin P. Vocal attractiveness increases by averaging.Curr. Biol. 2010; 20: 116-120Abstract Full Text Full Text PDF PubMed Scopus (101) Google Scholar, 9Bestelmeyer P.E. Latinus M. Bruckert L. Rouger J. Crabbe F. Belin P. Implicitly perceived vocal attractiveness modulates prefrontal cortex activity.Cereb. Cortex. 2012; 22: 1263-1270Crossref PubMed Scopus (30) Google Scholar, 10Latinus M. Belin P. Anti-voice adaptation suggests prototype-based coding of voice identity.Front Psychol. 2011; 2: 175Crossref PubMed Scopus (42) Google Scholar, 11Lavner Y. Rosenhouse J. Gath I. The Prototype Model in Speaker Identification by Human Listeners.Int. J. Speech Technol. 2001; 4: 63-74Crossref Scopus (33) Google Scholar]. Here, we show by using fMRI that voice identity is coded in the TVA as a function of acoustical distance to two internal voice prototypes (one male, one female)—approximated here by averaging a large number of same-gender voices by using morphing [12Kawahara, H., and Matsui, H. (2003). Auditory morphing based on an elastic perceptual distance metric in an interference-free time-frequency representation. In IEEE International Conference on Acoustics, Speech, and Signal Processing., Volume 1. pp. I-256-I-259 vol.251.Google Scholar]. Voices more distant from their prototype are perceived as more distinctive and elicit greater neuronal activity in voice-sensitive cortex than closer voices—a phenomenon not merely explained by neuronal adaptation [13Kahn D.A. Aguirre G.K. Confounding of norm-based and adaptation effects in brain responses.Neuroimage. 2012; 60: 2294-2299Crossref PubMed Scopus (16) Google Scholar, 14Grill-Spector K. Henson R. Martin A. Repetition and the brain: neural models of stimulus-specific effects.Trends Cogn. Sci. 2006; 10: 14-23Abstract Full Text Full Text PDF PubMed Scopus (1694) Google Scholar]. Moreover, explicit manipulations of distance-to-mean by morphing voices toward (or away from) their prototype elicit reduced (or enhanced) neuronal activity. These results indicate that voice-sensitive cortex integrates relevant acoustical features into a complex representation referenced to idealized male and female voice prototypes. More generally, they shed light on remarkable similarities in cerebral representations of facial and vocal identity.
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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) | 0.011 | 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 it