---
license: other
license_name: multiple
task_categories:
  - audio-classification
language:
  - en
tags:
  - audio
  - codec
  - speech
  - channel-degradation
  - deepfake-detection
  - acoustic-features
  - bicoherence
  - CELP
  - telecommunications
size_categories:
  - 100K<n<1M
---

# SSA Codec Degradation Study — Acoustic Feature Exports

**Moonscape Software | 2026**
*A companion to the Synthetic Speech Atlas (SSA)*

---

## Overview

This dataset quantifies the effect of 35 codec conditions on 80+ acoustic
features extracted from 7,500 biological speech clips. It answers the question:
**"Which acoustic features survive telecommunications codec compression, and which
are destroyed?"**

The corpus is the empirical foundation for channel-aware gate calibration in
deepfake audio detection. Every threshold in the SSA Gate 0 channel triage
architecture is derived from measurements in this dataset.

**262,463 rows | 35 codec conditions | 7,500 source clips | 4 speech corpora**

---

## Key Finding

**Phase-smear decoupling (bico_f0_f1) survives CELP codec compression at 96.3%.**

This is counterintuitive — CELP codecs (AMR-NB, GSM, G.711) completely destroy
and parametrically reconstruct the waveform. Yet the first formant bicoherence
is almost entirely preserved.

The physical reason: bico_f0_f1 measures **nonlinear quadratic phase coupling**
established at glottal closure. CELP codec operations are entirely **linear**.
Linear operations cannot create or destroy nonlinear phase relationships.

Contrast with modgd_var (spectral phase complexity — a linear property):

| Codec Family | bico_f0_f1 | modgd_var | bico retained | modgd retained |
|-------------|-----------|-----------|--------------|----------------|
| Source (biological) | 0.465 | 5.332 | 100% | 100% |
| EVS SWB 48kbps | 0.456 | 5.362 | 98.1% | 100.6% |
| Opus 32kbps | 0.465 | 5.361 | 99.9% | 100.5% |
| AMR-NB 4.75kbps | 0.446 | 2.697 | **95.8%** | **50.6%** |
| GSM 13kbps | 0.446 | 2.804 | 95.8% | 52.6% |
| G.711 A-Law | 0.447 | 2.686 | 96.1% | 50.4% |
| Codec2 700bps | 0.475 | 2.770 | 102.1% | 51.9% |

**Implication for deployment:** bico_f0_f1-based deepfake detection works on
telephony audio, VoIP intercepts, and any channel condition. The detection
boundary is architectural — synthetic speech never had a biological glottis —
not environmental.

---

## Dataset Structure

**Format:** Long — one row per clip per codec condition.
Use `codec_condition` column to filter to a specific codec.

```python
import pandas as pd
df = pd.read_parquet('ssa_codec_degradation_study.parquet')

# Compare CELP vs modern codecs on primary detection signal
df.groupby('is_celp')['bico_f0_f1'].mean()

# Full degradation curve for modgd_var
df.groupby('codec_condition')['modgd_var'].mean().sort_values()

# All AMR-NB 4.75kbps clips
amr = df[df['codec_condition'] == 'amr_nb_475']
```

---

## Source Corpora

| Pool | Corpus | N clips | Licence | Recording conditions |
|------|--------|---------|---------|---------------------|
| VCTK_mic1 | VCTK 0.92 (MKH800) | 1,500 | CC-BY-4.0 | Anechoic studio, high-bandwidth |
| VCTK_mic2 | VCTK 0.92 (AKG C535) | 1,500 | CC-BY-4.0 | Anechoic studio, standard mic |
| AMI | AMI Meeting Corpus | 3,000 | CC-BY-4.0 | Spontaneous conversational |
| CREMA-D | CREMA-D | 1,500 | ODC-BY | Emotional speech, controlled |

**RAVDESS excluded:** CC-BY-NC-SA-4.0 licence would propagate NC to entire
dataset. RAVDESS-derived results available in the NC variant of this release.

All clips stratified by gender, source corpus, and emotional valence to ensure
biological diversity across the codec degradation curves.

---

## Codec Conditions

### Single Codec (27 conditions)

| Condition | Family | Nom. Ceiling | Standard |
|-----------|--------|-------------|----------|
| source | Biological | — | Unencoded reference |
| evs_swb_48k | EVS-SWB | 16kHz | 3GPP TS 26.445 |
| evs_swb_nodtx | EVS-SWB | 16kHz | EVS without DTX |
| evs_24400 | EVS | 16kHz | 3GPP R12 |
| evs_24400_nodtx | EVS | 16kHz | EVS 24.4k without DTX |
| evs_9600 | EVS | 8kHz | 3GPP R12 |
| evs_9600_nodtx | EVS | 8kHz | EVS 9.6k without DTX |
| opus_32k | Opus-CELT | 16kHz | IETF RFC6716 |
| opus_16k | Opus-SILK | 16kHz | IETF RFC6716 |
| opus_6k | Opus-SILK | 8kHz | IETF RFC6716 |
| lc3 | LC3 | 16kHz | Bluetooth LE Audio |
| aac_64k | Perceptual | 16kHz | MPEG-4 |
| aac_32k | Perceptual | 16kHz | MPEG-4 |
| mp3_128k | Perceptual | 16kHz | MPEG-1 Layer III |
| mp3_32k | Perceptual | 16kHz | MPEG-1 Layer III |
| g722 | SB-ADPCM | 7kHz | ITU-T G.722 |
| amr_wb | CELP-WB | 7kHz | 3GPP AMR-WB |
| g726_32k | ADPCM | 4kHz | ITU-T G.726 |
| g726_24k | ADPCM | 4kHz | ITU-T G.726 |
| g726_16k | ADPCM | 4kHz | ITU-T G.726 |
| amr_nb_122 | CELP | 4kHz | 3GPP AMR-NB 12.2kbps |
| amr_nb_475 | CELP | 4kHz | 3GPP AMR-NB 4.75kbps |
| gsm | CELP | 4kHz | ETSI GSM 13kbps |
| ilbc | CELP | 4kHz | IETF RFC3951 |
| speex_8k | CELP | 4kHz | Xiph Speex 8kbps |
| g711_ulaw | PCM-Comp | 4kHz | ITU-T G.711 μ-Law |
| g711_alaw | PCM-Comp | 4kHz | ITU-T G.711 A-Law |
| codec2_700 | CELP | 4kHz | FreeDV Codec2 700bps |

### Tandem Chains (7 conditions)
Multi-hop codec degradation simulating real-world transmission paths:

| Condition | Chain | Final ceiling |
|-----------|-------|--------------|
| tandem_opus_32k_to_evs_24400 | Opus 32k → EVS 24.4k | 16kHz |
| tandem_evs_24400_to_amr_wb | EVS 24.4k → AMR-WB | 7kHz |
| tandem_opus_32k_to_amr_wb | Opus 32k → AMR-WB | 7kHz |
| tandem_amr_wb_to_g711_ulaw | AMR-WB → G.711 | 4kHz |
| tandem_evs_24400_to_amr_nb_475 | EVS 24.4k → AMR-NB 4.75k | 4kHz |
| tandem_evs_24400_to_g711_ulaw | EVS 24.4k → G.711 | 4kHz |
| tandem_opus_32k_to_g711_ulaw | Opus 32k → G.711 | 4kHz |

---

## Gate Calibration Reference

Empirically derived thresholds from this dataset:

| Feature | Source mean | CELP mean | Suggested threshold | Gate use |
|---------|------------|-----------|--------------------|---------| 
| modgd_var | 5.332 | 2.960 | **4.0** | Gate 0: below = CELP confirmed |
| bico_f0_f1 | 0.465 | 0.448 | N/A | Channel-agnostic — no gate needed |
| codec_cutoff_hz | 4393 | 2336 | **3000** | Provenance: below = NB ceiling |
| f1_velocity | 77.3 | 50.7 | **64.0** | Degrades under CELP |
| spectral_floor_var | 0.041 | 0.001 | **0.020** | Dead room / digital vacuum gate |
| pause_cv | 0.850 | 0.859 | N/A | Preserved — structural, not spectral |

---

## Citation

If you use this dataset please cite:

```
@dataset{moonscape_ssa_codec_2026,
  title     = {SSA Codec Degradation Study — Acoustic Feature Exports},
  author    = {Moonscape Software},
  year      = {2026},
  publisher = {HuggingFace},
  note      = {Export version SSA\_CodecStudy\_v1\_2026}
}
```

and cite the source corpora:
- VCTK: Yamagishi et al. (2019)
- AMI: Carletta et al. (2005)
- CREMA-D: Cao et al. (2014)

---

## Licence

**CC-BY-4.0** — source corpora are VCTK (CC-BY-4.0), AMI (CC-BY-4.0),
CREMA-D (ODC-BY). Commercial use permitted with attribution.
Academic and commercial licences available from Moonscape Software.

*SSA Codec Degradation Study v1 | Moonscape Software | 2026*
*Export version: SSA_CodecStudy_v1_2026*
*For full data dictionary see SSA_CODEC_STUDY_DATA_DICTIONARY.md*