Cross-Talk Detection in the IVAS Stereo Codec Based on GCC-PHAT
Bibliographic record
Abstract
In real-time teleconferences over mobile networks, cross-talk can significantly impact the performance of parametric stereo codecs, particularly at low bitrates. When multiple speakers overlap, stereo quality can be improved by independently encoding the left and right channels, especially when inter-channel correlation is low. This approach can be implemented using the dual-mono EVS coder, for example. The recently standardized 3GPP IVAS codec incorporates both a parametric stereo model and an independent left/right stereo model based on the dual-mono EVS codec. To address cross-talk, the 3GPP IVAS codec features a cross-talk classifier that uses a multivariate statistical model based on GCC-PHAT and other spatial cues, allowing for seamless switching between the two stereo models. Listening tests show that the IVAS stereo codec enhances performance in single-talker scenarios while maintaining quality in cross-talk segments.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".