SiangTTS VoxCPM2 Thai LoRA

--- license: cc-by-sa-4.0 base_model: openbmb/VoxCPM2 library_name: voxcpm pipeline_tag: text-to-speech language: - th - en tags: - text-to-speech - voice-cloning - thai - voxcpm - lora --- # SiangTTS — Thai Voice-Cloning TTS (VoxCPM2 LoRA) **SiangTTS** (เสียง = *voice*) is a LoRA adapter for [`openbmb/VoxCPM2`](https://huggingface.co/openbmb/VoxCPM2) that gives it clear, natural **Thai** speech with zero-shot **voice cloning**, trained on a single RTX 3090 (24 GB). It's a parameter-efficient (LoRA) fine-tune of VoxCPM2 — small enough to train on one consumer GPU while keeping the base model's voice-design and cloning abilities. The Thai-adaptation approach is inspired by **JaiTTS** (a separate, closed-source Thai VoxCPM model by others); SiangTTS is an independent open reproduction at LoRA scale and is not affiliated with it. 🔊 **Listen / compare (ref vs ground-truth vs base vs SiangTTS):** <https://dubbing-ai.github.io/VoxCPM-thai/> · Code: <https://github.com/dubbing-ai/VoxCPM-thai> ## Results Measured with **Typhoon-Whisper-Large-v3** (Thai ASR; CER) and **WavLM** x-vectors (speaker SIM) on small eval sets, so numbers are directional. CER is an *upper bound on error* — the ASR judge itself mis-recognises some rare/archaic Thai words the model pronounces correctly. VoxCPM2's base is already a capable Thai speaker (it reads numerals and handles long-form). **SiangTTS clones at essentially the real same-speaker similarity ceiling and is as intelligible as the original recordings**, with much lower CER than the base. The `GT` column is the real recording, included as the reference. | Voice cloning (80 prompts) | GT (real rec.) | Base | **SiangTTS** | |---|---|---|---| | Intelligibility — CER ↓ | 0.97% | 3.26% | **0.84%** | | Speaker similarity — SIM ↑ | 0.913 | 0.906 | **0.909** | (CER ≤ GT reflects clean, ASR-friendly synthesis plus the ASR judge's own floor; SIM ≈ GT means cloning is about as close as two real recordings of one speaker.) Separately, short-form Thai CER 5.7%→3.8% and long-form 2.7%→1.6% (small 5 / 2 -prompt sets — directional). Trained 2 epochs over ~205 h: Common Voice Thai (diverse speakers) + porjai_central (studio-clean) + a LibriTTS-R English slice (retains English & code-switching). Audio encoded at 16 kHz, generated at 48 kHz (VoxCPM2 design). ## Usage ```python from voxcpm import VoxCPM from voxcpm.model.voxcpm2 impo...

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