Combining equalization and estimation for bandwidth extension of narrowband speech
Bibliographic record
Abstract
Current public telephone networks compromise voice quality by bandlimiting the speech signal. Telephone speech is characterized by a bandpass response from 300 to 3400 Hz. The voice quality is perceived as being much worse than for wideband speech (50-7000 Hz). We present a novel approach which combines equalization and estimation to create a wideband signal, with reconstructed components in the 3400 Hz to 7000 Hz range. Equalization is used in the 3400-4000 Hz range. Its performance is better than statistical estimation procedures, because the mutual dependencies between the narrowband and highband parameters are not sufficiently large. Subjective evaluation using an improvement category rating shows that the reconstructed wideband speech using both equalization and estimation substantially enhances the quality of telephone speech. We have also evaluated the performance on the narrowband output of several standard codecs. Overall, the use of equalization for part of the highband regeneration makes the system more robust to phonetic variability and speaker gender.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".