For one reference voice: every emotion at four intensity/containment settings, every VoiceNet dimension at four levels, edge cases and style variants — in English and German from the same sentence, so the pairs can train a speech-to-speech model that preserves speaker and emotion.
- Design manual — the full condition matrix, which adapter at which merge strength for which emotion/dimension, prompt templates, ranking formulas, metadata schema, safety gate, compute estimates.
- Demo grid — 808 conditions for one voice, generated twice (standard vs 25 % Mediathek merge), side by side with the reference. 1,617 clips.
- Execution protocol — every step, adapter, prompt and setting actually used, with per-dimension results.
808 groups/voice · 323,200 generations per profile · 646,917 candidates stored · 152 GPU-hours · 2,126 generations/GPU-hour.
Extrapolated: 100 voices ≈ 1,226 GPU-h · 1,000 ≈ 12,260 · 6,000 ≈ 73,600 GPU-h and ~17 TB. 6,000 at the full matrix is not feasible as one run; see the manual for the proposed subsets.
- German conditioning holds the speaker far less well than English — mean speaker similarity 0.578 (EN) vs 0.376 (DE) over 323,200 candidates. This is the central obstacle for the DE↔EN goal.
- Intensity, not containment, breaks the voice clone: intense conditions 0.088 lower, with 19.4 % below the usable floor vs 0.0 % for moderate.
- The 25 % Mediathek merge is near-null: +0.008 speaker similarity, no change to composite, WER, genuineness, blend or emotion strength.
- Voice conversion is not free where it is most needed: on 271 badly drifted clips it raised similarity 0.381 → 0.623 on all of them but cost −0.109 DNSMOS, and only 12 % passed the published keep rule.
No human listening study — all numbers come from an automatic sensor stack that agrees with a listener at only about ρ ≈ +0.21 on spoken material. The four-level VoiceNet ladder, the A/B/C/D stage directions and the domain labels are this project's own constructions, documented as such in the manual.
Base model: laion/moss-tts-local-transformer-4.55b-voice-acting-v2.