| import os |
| import gradio as gr |
| import soundfile as sf |
| from huggingface_hub import snapshot_download |
|
|
| MODEL_REPO = "LyngualLabs/YorubaEnglish-CodeSwitching-TTS" |
| DEFAULT_REF_WAV = "reference.wav" |
| DEFAULT_REF_TEXT = "Ìròyìn ti sọ pé the government will ensure electricity tariff goes down ní January." |
|
|
| print("Downloading model...", flush=True) |
| model_dir = snapshot_download(MODEL_REPO) |
|
|
| from voxcpm import VoxCPM |
|
|
| print("Loading model...", flush=True) |
| model = VoxCPM.from_pretrained(model_dir, load_denoiser=False) |
| SR = model.tts_model.sample_rate |
| print("Model loaded.", flush=True) |
|
|
|
|
| def synthesize(text, ref_audio, ref_text, cfg_value, inference_timesteps): |
| if not text or not text.strip(): |
| raise gr.Error("Please enter some text to synthesize.") |
|
|
| prompt_wav_path = ref_audio if ref_audio else DEFAULT_REF_WAV |
| prompt_text = ref_text.strip() if (ref_audio and ref_text and ref_text.strip()) else ( |
| DEFAULT_REF_TEXT if not ref_audio else "" |
| ) |
| if ref_audio and not prompt_text: |
| raise gr.Error("Please provide the exact transcript of your uploaded reference audio.") |
|
|
| wav = model.generate( |
| text=text.strip(), |
| prompt_wav_path=prompt_wav_path, |
| prompt_text=prompt_text, |
| cfg_value=cfg_value, |
| inference_timesteps=int(inference_timesteps), |
| ) |
| out_path = "output.wav" |
| sf.write(out_path, wav, SR) |
| return out_path |
|
|
|
|
| EXAMPLES = [ |
| ["Mo ní meeting pẹ̀lú marketing team ní aago mẹ́wàá lónìí, nítorí náà ẹ jẹ́ ká yára."], |
| ["Ìròyìn ti sọ pé the government will ensure electricity tariff goes down ní January."], |
| ["Wọ́n ní ìpàdé ní hotel tó wà ní Victoria Island, kì í ṣe ní office wa."], |
| ] |
|
|
| with gr.Blocks(title="Yoruba-English Code-Switching TTS") as demo: |
| gr.Markdown( |
| """ |
| # 🎙️ Yoruba–English Code-Switching TTS |
| A voice-cloning text-to-speech model for Yoruba, including natural |
| Yoruba–English code-switching — full fine-tuned from |
| [VoxCPM2](https://huggingface.co/openbmb/VoxCPM2) on ~1,039 hours pooled from |
| DSN African Voices, NaijaVoices, YECS, and WAXAL. |
| |
| Model card: [LyngualLabs/YorubaEnglish-CodeSwitching-TTS](https://huggingface.co/LyngualLabs/YorubaEnglish-CodeSwitching-TTS) |
| |
| ⚠️ **Experimental** — trained for only ~1 epoch. Quality varies by sentence; |
| rarer words/proper nouns are more likely to be mispronounced. |
| """ |
| ) |
| with gr.Row(): |
| with gr.Column(): |
| text_in = gr.Textbox( |
| label="Text to speak", |
| placeholder="Type Yoruba, English, or mixed Yoruba-English text...", |
| lines=4, |
| ) |
| with gr.Accordion("Voice cloning (optional) — upload your own reference", open=False): |
| ref_audio = gr.Audio(label="Reference audio (3-10s, clean)", type="filepath") |
| ref_text = gr.Textbox(label="Exact transcript of the reference audio") |
| gr.Markdown("_Leave blank to use the default built-in voice._") |
| with gr.Accordion("Advanced", open=False): |
| cfg_value = gr.Slider(1.0, 4.0, value=2.0, step=0.1, label="cfg_value (higher = sticks closer to reference)") |
| inference_timesteps = gr.Slider(10, 35, value=22, step=1, label="inference_timesteps (higher = smoother, slower)") |
| btn = gr.Button("Generate", variant="primary") |
| with gr.Column(): |
| audio_out = gr.Audio(label="Generated speech", type="filepath") |
|
|
| gr.Examples(examples=EXAMPLES, inputs=[text_in]) |
| btn.click( |
| synthesize, |
| inputs=[text_in, ref_audio, ref_text, cfg_value, inference_timesteps], |
| outputs=[audio_out], |
| ) |
|
|
| if __name__ == "__main__": |
| demo.launch() |
|
|
