Add MOSS-TTS engine family and finalize native TTSD behavior Release details: - Integrate Local/Delay/TTSD MOSS models into unified nodes - Finalize strict native TTSD incompatibility handling - Improve native SRT behavior and user-facing error propagation
6.1 KiB
6.1 KiB
TTS Engines Reference Tables
Engine Comparison
| Engine | Models | Size | TTS | SRT | VC | ASR | Training | License | Special Features | Languages |
|---|---|---|---|---|---|---|---|---|---|---|
| F5-TTS | Base, v1, E2TTS + 8 lang models | ~1.2GB each | ✅ | ✅ | ❌ | ❌ | ❌ | CC-BY-NC-4.0 | Targeted Word/Speech Editing, Speed control | 🇺🇸🇩🇪🇪🇸🇫🇷🇮🇹🇯🇵🇧🇷🇵🇱🇮🇳🇹🇭 |
| ChatterBox | EN, DE×3, IT, FR, RU, HY, KA, JA, KO, NO | ~4.3GB | ✅ | ✅ | ✅ | ❌ | ❌ | MIT | Expressiveness slider | 🇺🇸🇩🇪🇫🇷🇮🇹🇯🇵🇰🇷🇷🇺🇳🇴🇦🇲🇬🇪 |
| ChatterBox 23L | v1, v2, Vietnamese (Viterbox), Egyptian Arabic (oddadmix) | ~4.3GB | ✅ | ✅ | ✅ | ❌ | ❌ | MIT | 24 languages in single model, emotion tokens (v2 - doesn't work) | 🇺🇸🇨🇳🇩🇪🇪🇸🇫🇷🇮🇹🇯🇵🇰🇷🇷🇺🇵🇹🇵🇱🇮🇳🇪🇬🇹🇷🇹🇭🇳🇴🇻🇳🇩🇰🇫🇮🇬🇷🇮🇱🇲🇾🇳🇱🇸🇪🇰🇪(+9) |
| VibeVoice | 1.5B, 7B, KugelAudio-0 (7B), kugel-2 (7B), Hindi-1.5B/7B | 5.4GB / 18GB | ✅ | ✅ | ❌ | ❌ | ❌ | MIT (research-only per model card) | 90-min long-form, Native 4-speaker (Base models), Multilingual (KugelAudio variants), 4-bit quantization | 🇺🇸🇨🇳🇩🇪🇪🇸🇫🇷🇮🇹🇯🇵🇰🇷🇷🇺🇧🇷🇵🇱🇮🇳🇪🇬🇹🇷🇹🇭🇳🇴🇻🇳🇦🇲🇬🇪🇩🇰🇫🇮🇬🇷🇮🇱🇲🇾🇳🇱🇸🇪🇰🇪 |
| Higgs Audio 2 | 3B | ~9GB | ✅ | ✅ | ❌ | ❌ | ❌ | Boson Higgs Audio 2 Community License | 3 multi-speaker, CUDA graphs (55+ tokens/sec) | 🇺🇸🇨🇳🇩🇪🇪🇸🇰🇷 |
| IndexTTS-2 | IndexTTS-2 | ~4.7GB | ✅ | ✅ | ❌ | ❌ | ❌ | bilibili Model Use License | Emotion Control: 8 vectors, Text as reference, Audio as reference | 🇺🇸🇨🇳🇯🇵 |
| CosyVoice3 | 0.5B, 0.5B-RL | ~5.4GB | ✅ | ✅ | ✅ | ❌ | ❌ | Apache-2.0 | Paralinguistic tags | 🇺🇸🇨🇳🇯🇵🇰🇷 |
| Qwen3-TTS | 0.6B, 1.7B (CustomVoice/VoiceDesign/Base) | ~3-6GB | ✅ | ✅ | ❌ | ✅ | ❌ | Apache-2.0 | Voice design, ASR (Automatic Speech Recognition) | 🇺🇸🇨🇳🇩🇪🇪🇸🇫🇷🇮🇹🇯🇵🇰🇷🇷🇺🇵🇹 |
| Granite ASR | granite-4.0-1b-speech | ~4.6GB | ❌ | ✅ | ❌ | ✅ | ❌ | Apache-2.0 | ASR (Automatic Speech Recognition), Custom timestamps/SRT via reused Qwen forced aligner, Speech translation (experimental) | 🇺🇸🇩🇪🇪🇸🇫🇷🇯🇵🇵🇹 |
| Step Audio EditX | 3B LLM + CosyVoice | ~7GB | ✅ | ✅ | ❌ | ❌ | ❌ | Apache-2.0 (verify before commercial use) | Second Pass Speech Editing Node: 14 emotions, 32 speaking styles, Paralinguistic effects | 🇺🇸🇨🇳🇯🇵🇰🇷 |
| Echo-TTS | echo-tts-base + fish-s1-dac-min | ~5.3GB + ~1.8GB | ✅ | ✅ | ❌ | ❌ | ❌ | CC-BY-NC-SA-4.0 | Diffusion-based (~30s best), Force Speaker KV (speaker drift control) | 🇺🇸 |
| MOSS-TTS | Local 1.7B, Delay 8B, TTSD 8B | ~8.5GB tokenizer + ~6.1GB/17GB/18GB model | ✅ | ✅ | ❌ | ❌ | ❌ | Apache-2.0 | Zero-shot voice cloning, 20-language generation, Long-form TTSD, Native 1-5 speaker TTSD dialogue, Duration token hint, Local/Delay/TTSD variants | 🇺🇸🇨🇳🇩🇪🇪🇸🇫🇷🇮🇹🇯🇵🇰🇷🇷🇺🇧🇷🇵🇱🇪🇬🇹🇷🇩🇰🇬🇷🇸🇪 |
| RVC | Community .pth | 100-300MB | ❌ | ❌ | ✅ | ❌ | ✅ | MIT (framework); community models vary | Real-time VC, Integrated training workflow, Pitch shift (±14), 6 HuBERT models, Language-independent | 🇺🇸🇨🇳🇩🇪🇪🇸🇫🇷🇮🇹🇯🇵🇰🇷🇷🇺🇧🇷🇵🇱🇮🇳🇪🇬🇹🇷🇹🇭🇳🇴🇻🇳🇦🇲🇬🇪🇩🇰🇫🇮🇬🇷🇮🇱🇲🇾🇳🇱🇸🇪🇰🇪 |