Test Matrix
- Browsers: Chrome 121, Edge 121.
- Hardware: recent laptop GPU (WebGPU path) and 8‑core CPU (WASM path).
- Segments: 5s, 12s, 20s; batch of 10 lines.
Key Results
- WebGPU reduces median latency by ~1.5×–3× for 8–20s segments.
- WASM with threads/SIMD remains competitive for ≤8s lines and broad compatibility.
- Chrome and Edge results are within ±10% on identical hardware; pick your ecosystem preference.
Segmentation Strategy
Segment by meaning, not time. Keep each unit under ~20 seconds, and avoid over‑long paragraphs. This approach keeps memory pressure low and improves perceived pacing.
Practical Profiles
// Creator profile (WebGPU)
Chrome 121 + WebGPU → 10–15s lines → WAV export → Mastering (−16 LUFS) → Publish
// Managed laptop profile (WASM)
Edge 121 + WASM threads/SIMD → 8–12s lines → WAV export → ffmpeg join → Publish
Stability Tips
- Keep one active tab for generation during long sessions.
- Restart the tab between 30–40 segments to reclaim memory.
- Export per segment to minimize redo cost on errors.
What to Measure
- Per‑segment synthesis time and standard deviation.
- First‑load vs cached model load time.
- Audio artifacts after mastering (peak, LUFS, de‑esser activity).
Takeaways
- Prefer WebGPU when available; WASM is a solid universal baseline.
- Segmentation improves both stability and editorial quality.
- Standardize loudness to deliver consistent user experience.
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Author: Kokoro Web Team • Last updated 2025‑01‑15