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8104203 355d903 8104203 355d903 185fc75 70399da 43f2732 70399da 43f2732 de18ed9 43f2732 3abac7b 43f2732 70399da 43f2732 8104203 70399da 43f2732 3abac7b 43f2732 70399da 2c6febe c741ce2 70399da 185fc75 70399da | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | import spaces
import torch
torch.manual_seed(160923)
_orig_set_device = torch.cuda.set_device
def _safe_set_device(device):
try:
_orig_set_device(device)
except RuntimeError as exc:
if "Low-level CUDA init" in str(exc):
return
raise
torch.cuda.set_device = _safe_set_device
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]
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)
controllable_ui = self.controllable_ui
@spaces.GPU
def read(prompt, language, prosody_creativity, duration_scaling_factor, voice_seed, emb1, reference_audio):
iso = language.split(" ")[-1].split("(")[1].split(")")[0]
sr, wav, fig = controllable_ui.read(prompt,
reference_audio,
iso,
iso,
voice_seed,
prosody_creativity,
duration_scaling_factor,
1.,
1.0,
1.0,
emb1,
0.,
0.,
0.,
0.,
0.,
-24.)
return (sr, float2pcm(wav)), fig
self.iface = gr.Interface(fn=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)"),
],
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()
if __name__ == '__main__':
TTSWebUI(gpu_id="cuda" if torch.cuda.is_available() else "cpu")
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