Fine-tuning Qwen3-TTS With Emotion Tags — and Emotion Vectors That Transfer Across Speakers
ProfessionalHorse707 · reddit · 2026-09-10
A developer fine-tuned Qwen3-TTS with inline transcript control tags (teacher-student distillation over 74k clips, LoRA) and open-sourced the model. Key lessons: mixed codec language prefixes fix buzzing artifacts, and high vLLM concurrency corrupts prosody. Surprisingly, emotion behaves roughly affinely in speaker-embedding space — per-emotion task vectors computed from centroids can transfer emotion control to arbitrary cloned voices without per-speaker training.
More from Multimodal
- One prompt, full Blender animation: dev says he never touched Blender once — iamfakhrealam · 2026-10-26
- Dense instance segmentation via Muse Wonder + SAM 3.1 on Meta's Model API — nikhilaravi · 2026-10-26
- LichtFeld Studio v0.5.4.3 ships community-built SteadySplats, POPSpa and Voxelization — janusch_patas · 2026-10-26
- One prompt to a 2-3 min narrated short: hands-on test of Antigravity video generation — AI_Andrew · 2026-10-26
- Creator makes 10,564-frame animated short entirely with Gemini toolchain — AI_Andrew · 2026-10-26
- FLUX.3 Klein step-distilled to 4-8 steps with CFG baked in — Fit-Structure-6489 · 2026-10-26