Hearing Two Things at Once: Neurophysiological Indices of Speech Segregation and Identification
Bibliographic record
Abstract
The discrimination of concurrent sounds is paramount to speech perception. During social gatherings, listeners must extract information from a composite acoustic wave, which sums multiple individual voices that are simultaneously active. The observers' ability to identify two simultaneously presented vowels improves with increasing separation between the fundamental frequencies (f0) of the two vowels. Event-related potentials to stimuli presented during attend and ignore conditions revealed activity between 130 and 170 msec after sound onset that reflected the f0 differences between the two vowels. Another, more posterior and right-lateralized, negative wave maximal at 250 msec, and a central-parietal slow negativity were observed only during vowel identification and may index stimulus categorization. This sequence of neural events supports a multistage model of auditory scene analysis in which the spectral pattern of each vowel constituent is automatically extracted and then matched against representations of those vowels in working memory.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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".