Low complexity, low delay speech coding for indoor wireless communications
Bibliographic record
Abstract
The paper presents a low complexity, low delay variable rate speech coding method suitable for low power (CDMA or TDMA) indoor wireless communications. The indoor wireless communications channel is characterized by relatively deep fades resulting in bursty errors. A robust speech codec is required to combat this bursty nature. Low power operation is essential, which negates the applicability of LD-CELP (G.728) for indoor wireless applications, Historically, ADPCM (G.721) has been proposed, which lacks robustness to random and bursty errors and has a relatively high bit rate (32 kb/s). To circumvent the need for relatively complex echo-cancellation, low end to end delays are required which implies that interleaving is not applicable. In the paper, a low complexity, low delay, variable rate CELP algorithm is proposed and techniques to improve the robustness to bursty errors are investigated. The new technique is compared to ADPCM on the basis of complexity and performance (MOS) over measured indoor wireless channels at 1.7 GHz with various combinations of space, frequency and code diversity.>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".