voxcpm-afrispeech-full-inference-20260606

VoxCPM — AfriSpeech Multilingual TTS (50 African Languages)

Full fine-tune of openbmb/VoxCPM-0.5B on all 50 language subsets of AfriSpeech/africa-speech, merged into a single training manifest (mono 16 kHz WAV).

Try it live: AfriSpeech/VoxCPM-AfriSpeech

Supported languages

Afar, Akan (Twi), Amharic, Baoule, Bemba, Burkina Faso Fulfulde, Dan, Ewe, Fon, Fulani, Ganda (Luganda), Hausa, Igbo, Jola-Kasa, Kalanga, Kalenjin, Kikuyu, Lingala, Lozi, Luba-Lulua, Makhuwa-Shirima, Malgache, Mankanya, Mbunda, Mende, Mossi, Ngambay, Northeastern Dinka, Nyanja, Oromo (Borana-Arsi-Guji), Pular, Punu, Rundi (Kirundi), Rwandan (Kinyarwanda), Sango, Shilluk, Shona, Somali, Sukuma, Swahili, Tarifit, Tashelhayt, Tigrinya, Tiv, Tumbuka, West Central Oromo, Western Niger Fulfulde, Wolof (Senegal), Yaka, Yoruba.

Training details

Weights are stored as pytorch_model.bin wrapped in {"state_dict": ...} — the format VoxCPM.from_pretrained() expects. Optimizer/scheduler states are not included.

Usage

from voxcpm import VoxCPM
import soundfile as sf

model = VoxCPM.from_pretrained("AfriSpeech/voxcpm-afrispeech-full-inference-20260606")

wav = model.generate(
    text="Karibu sana! Tunafurahi kukuona hapa leo.",
    inference_timesteps=10,
    cfg_value=2.0,
)
sf.write("out.wav", wav, 16000)

For voice cloning, pass prompt_wav_path and prompt_text (a 3–10 s reference clip and its transcript) to model.generate(...).

Related

• Demo Space: AfriSpeech/VoxCPM-AfriSpeech
• Source dataset: AfriSpeech/africa-speech
• Base model: openbmb/VoxCPM-0.5B