An adaptive playout algorithm with delay spike detection for real-time VoIP
Why this work is in the frame
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Bibliographic record
Abstract
As the Internet is a best-effort delivery network, audio packets may be delayed or lost en route to the receiver due to network congestion. To compensate for the variation in network delay, audio applications buffer received packets before playing them out. Basic algorithms adjust the packet play out time during periods of silence such that all packets within a talkspurt are equally delayed. Another approach is to scale individual voice packets using dynamic time-scale modification. In this work, an adaptive playout algorithm based on the normalized least mean square algorithm, is improved by introducing a spike-detection mode to rapidly adjust to delay spikes. Simulations on Internet traces show that the enhanced bi-modal playout algorithm improves performance by reducing both the average delay and the loss rate as compared to the original algorithm.
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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 | 0.000 | 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