Blind source separation in a distributed microphone meeting environment for improved teleconferencing
Why this work is in the frame
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Bibliographic record
Abstract
From an audio perspective, the present state of teleconferencing technology leaves something to be desired; speaker overlap is one of the causes of this inadequate performance. To that end, this paper presents a frequency-domain implementation of convolutive BSS specifically designed for the nature of the teleconferencing environment. In addition to presenting a novel depermutation scheme, this paper presents a least-squares post-processing scheme, which exploits segments during which only a subset of all speakers are active. Experiments with simulated and real data demonstrate the ability of the proposed methods to provide SIRs at or near that of the adaptive noise cancellation (ANC) solution which is obtained under idealistic assumptions that the ANC filters are adapted with one source being on at a time.
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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 | 0.001 | 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 | 0.001 |
| 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