A multifilter approach to acoustic echo cancellation
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Bibliographic record
Abstract
Hands-free teleconferencing is increasingly frequent today. An important design consideration for any such communication tool that uses high-quality audio is the return echo caused by the acoustic coupling between the loudspeakers and microphones at each end of the conference. An echo-suppression filter (ESF) reduces the level of this return echo, increasing speech intelligibility. A new ESF has been designed based on a block frequency domain adaptive filter using the well-known least-mean-square (LMS) criteria. There are two important coefficients in LMS adaptive filters which affect how an ESF adapts to changing acoustic conditions at each end of the conference, such as double-talk conditions and moving electroacoustic transducers. Previous approaches to similar ESFs have used either a single or double pair of these coefficients, whereas the new model typically uses ten. The performance of single, double, and multifilter architectures was compared. Performance was evaluated using both empirical measurements and subjective listening tests. Speech and music were used as the stimuli for a two-way teleconferencing experiment. The new filter performed better than the single- and two-filter ESF designs, especially in conferencing conditions with frequent double talk, and the new ESF can be optimized to suit different acoustic situations.
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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 | 0.001 | 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