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import spaces
import gradio as gr
import torch
from TTS.api import TTS
import os
import json
os.environ["COQUI_TOS_AGREED"] = "1"
device = "cuda"
tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(device)
@spaces.GPU(enable_queue=True)
def clone(text, audio):
# Generowanie mowy
wav = tts.tts(text=text, speaker_wav=audio, language="pl")
# Zapisywanie pliku audio
tts.save_wav(wav, file_path="./output.wav")
# Uzyskanie informacji o fonemach
phonemes_info = tts.synthesizer.get_phonemes(text, language="pl")
# Przygotowanie informacji o fonemach
phonemes_data = []
for phoneme, duration in phonemes_info:
phonemes_data.append({
"phoneme": phoneme,
"duration": float(duration)
})
# Zapisywanie informacji o fonemach do pliku JSON
with open("./phonemes_info.json", "w", encoding="utf-8") as f:
json.dump(phonemes_data, f, ensure_ascii=False, indent=2)
return "./output.wav", "./phonemes_info.json"
# Interfejs Gradio
iface = gr.Interface(
fn=clone,
inputs=[
gr.Textbox(label='Tekst do syntezy'),
gr.Audio(type='filepath', label='Plik audio z głosem referencyjnym')
],
outputs=[
gr.Audio(type='filepath', label='Zsyntezowana mowa'),
gr.File(label='Informacje o fonemach (JSON)')
],
title='Klonowanie Głosu z Informacjami o Fonemach',
theme=gr.themes.Base(primary_hue="teal", secondary_hue="teal", neutral_hue="slate")
)
iface.launch(share=True) |