Description of ITU-T Recommendation G.729 Annex A: reduced complexity 8 kbit/s CS-ACELP codec
Bibliographic record
Abstract
This paper describes the recently adopted ITU-T Recommendation G.729 Annex A (G.729A) for encoding speech signals at 8 kbit/s with low complexity. G.729A has been selected as the standard speech coding algorithm for multimedia digital simultaneous voice and data (DSVD). G.729A is bitstream interoperable with G.729; i.e., speech coded with G.729A can be decoded with G.729, and vice versa. As G.729, it uses the conjugate structure algebraic code excited linear prediction (CS-ACELP) algorithm with 10 ms frames. However, several algorithmic changes have been introduced into G.729 which resulted in 50% drop in its complexity, enabling a DSP implementation with a complexity of about 10-12 MIPS. This paper describes the algorithmic changes which have been introduced in order to achieve the low complexity goal while meeting the terms of reference. Subjective tests have been performed by ITU-T in both the selection phase and the characterization phase and the results showed that the performance of G.729A is equivalent to both G.729 and G.726 at 32 kbit/s in most operating conditions; however, it is slightly worse in case of three tandems and in the presence of background noise. A breakdown of the complexities of both G.729 and G.729A is given at the end of the paper.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.066 |
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".