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Running
on
T4
| import torch | |
| torch.manual_seed(160923) | |
| import gradio as gr | |
| import torch.cuda | |
| from huggingface_hub import hf_hub_download | |
| from InferenceInterfaces.ControllableInterface import ControllableInterface | |
| from Utility.utils import float2pcm | |
| from Utility.utils import load_json_from_path | |
| class TTSWebUI: | |
| def __init__(self, | |
| gpu_id="cpu", | |
| title="Controllable Text-to-Speech for over 7000 Languages", | |
| article="The biggest thank you to Hugging Face🤗 for sponsoring the GPU for this space! <br> To get the code, models, additional features, and more information, check out our toolkit: https://github.com/DigitalPhonetics/IMS-Toucan <br>", | |
| tts_model_path=None, | |
| vocoder_model_path=None, | |
| embedding_gan_path=None, | |
| available_artificial_voices=10 # be careful with this, if you want too many, it might lead to an endless loop | |
| ): | |
| path_to_iso_list = hf_hub_download(repo_id="Flux9665/ToucanTTS", filename="iso_to_fullname.json") | |
| iso_to_name = load_json_from_path(path_to_iso_list) | |
| text_selection = [f"{iso_to_name[iso_code]} ({iso_code})" for iso_code in iso_to_name] | |
| # accent_selection = [f"{iso_to_name[iso_code]} Accent ({iso_code})" for iso_code in iso_to_name] | |
| self.controllable_ui = ControllableInterface(gpu_id=gpu_id, | |
| available_artificial_voices=available_artificial_voices, | |
| tts_model_path=tts_model_path, | |
| vocoder_model_path=vocoder_model_path, | |
| embedding_gan_path=embedding_gan_path) | |
| self.iface = gr.Interface(fn=self.read, | |
| inputs=[gr.Textbox(lines=2, | |
| placeholder="write what you want the synthesis to read here...", | |
| value="What I cannot create, I do not understand.", | |
| label="Text input"), | |
| gr.Dropdown(text_selection, | |
| type="value", | |
| value='English (eng)', | |
| label="Select the Language of the Text (type on your keyboard to find it quickly)"), | |
| gr.Slider(minimum=0.0, maximum=0.8, step=0.1, value=0.5, label="Prosody Creativity"), | |
| gr.Slider(minimum=0.7, maximum=1.3, step=0.1, value=1.0, label="Faster - Slower"), | |
| gr.Slider(minimum=0, maximum=available_artificial_voices, step=1, value=5, label="Random Seed for the artificial Voice"), | |
| gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Gender of artificial Voice"), | |
| gr.Audio(type="filepath", show_label=True, container=True, label="[OPTIONAL] Voice to Clone (if left empty, will use an artificial voice instead)"), | |
| # gr.Slider(minimum=0.5, maximum=1.5, step=0.1, value=1.0, label="Pitch Variance Scale"), | |
| # gr.Slider(minimum=0.5, maximum=1.5, step=0.1, value=1.0, label="Energy Variance Scale"), | |
| # gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Voice Depth") | |
| ], | |
| outputs=[gr.Audio(type="numpy", label="Speech"), | |
| gr.Image(label="Visualization")], | |
| title=title, | |
| allow_flagging="never", | |
| description=article, | |
| theme=gr.themes.Ocean(primary_hue="amber", secondary_hue="orange")) | |
| self.iface.launch() | |
| def read(self, | |
| prompt, | |
| language, | |
| prosody_creativity, | |
| duration_scaling_factor, | |
| voice_seed, | |
| emb1, | |
| reference_audio, | |
| # pitch_variance_scale, | |
| # energy_variance_scale, | |
| # emb2 | |
| ): | |
| sr, wav, fig = self.controllable_ui.read(prompt, | |
| reference_audio, | |
| language.split(" ")[-1].split("(")[1].split(")")[0], | |
| language.split(" ")[-1].split("(")[1].split(")")[0], | |
| voice_seed, | |
| prosody_creativity, | |
| duration_scaling_factor, | |
| 1., | |
| 1.0, | |
| 1.0, | |
| emb1, | |
| 0., | |
| 0., | |
| 0., | |
| 0., | |
| 0., | |
| -24.) | |
| return (sr, float2pcm(wav)), fig | |
| if __name__ == '__main__': | |
| TTSWebUI(gpu_id="cuda" if torch.cuda.is_available() else "cpu") | |