The relation between speech segment selectivity and source localization accuracy
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Bibliographic record
Abstract
An experimental analysis of the relation between speech signal segment power and the source direction-of-arrival-estimation accuracy is conducted. A total of 10 different speakers, including both male and female speakers, totaling to approximately 2 hours of speech are used to analyze the performance of the Phase Transform, the Maximum Likelihood, and the Unfiltered Cross Correlation time-delay estimation techniques. For female speakers, it is determined that the Phase Transform technique has a lower percentage of anomalies and a lower direction-of-arrival root mean-square error (DOA RMSE). Conversely, for male speakers, it is determined that the Unfiltered Cross Correlation has a lower percentage of anomalies although the Phase Transform has a lower DOA RMSE. The spatial distribution of the errors as well as the speech segment power relation to the errors are also presented.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 it