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import gradio as gr | |
import tempfile | |
from TTS.utils.synthesizer import Synthesizer | |
from huggingface_hub import hf_hub_download | |
REPO_ID = "ayymen/Coqui-TTS-Vits-shi" | |
my_title = "Tamazight Text-to-Speech" | |
my_description = "This model is based on [VITS](https://github.com/jaywalnut310/vits), thanks to 🐸 [Coqui.ai](https://coqui.ai/)." | |
my_examples = [ | |
["ⴰⵣⵓⵍ"], | |
["ⴰⵔ ⴽⵎ ⵜⵜⵉⵔⵉⵖ"], | |
["ⴳⵏ! ⴰⴷ ⴰⴽ ⵉⵙⵙⴳⵏ ⵕⴱⴱⵉ ⵉⵜⵜⵓ ⴽ."] | |
] | |
my_inputs = [ | |
gr.Textbox(lines=5, label="Input Text"), | |
] | |
my_outputs = gr.Audio(type="filepath", label="Output Audio") | |
def tts(text: str): | |
best_model_path = hf_hub_download(repo_id=REPO_ID, filename="best_model.pth") | |
config_path = hf_hub_download(repo_id=REPO_ID, filename="config.json") | |
# init synthesizer | |
synthesizer = Synthesizer( | |
best_model_path, | |
config_path, | |
use_cuda=True | |
) | |
# create audio file | |
wavs = synthesizer.tts(text) | |
with tempfile.NamedTemporaryFile(suffix = ".wav", delete = False) as fp: | |
synthesizer.save_wav(wavs, fp) | |
return fp.name | |
iface = gr.Interface( | |
fn=tts, | |
inputs=my_inputs, | |
outputs=my_outputs, | |
title=my_title, | |
description = my_description, | |
examples = my_examples, | |
cache_examples=True | |
) | |
iface.launch() | |