On the perceptual performance limitations of echo cancellers in wideband telephony
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, standard echo canceller performance measures are evaluated in terms of psychoacoustic aspects of human hearing. The focus is on wideband speech communications systems with long round-trip delays of 200 ms and up present in the transmission path. The results of a simple acoustic echo cancellation experiment are analyzed with a standard psychoacoustic model, revealing that steady-state echo return loss enhancement and mean square error cannot be used to determine whether residual echo is perceivable in the presence of background noise. In addition, a simple modification to the normalized least mean square (NLMS) algorithm is introduced by adding a perceptual preemphasis filter. Simulation results and listening tests show that it is possible to improve the perceived performance of an echo canceller during convergence by placing greater emphasis on frequencies at which the human auditory system is most sensitive.
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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 | 0.001 |
| 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 it