tts-xtts2-multi / app.py
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import io
import os
import tempfile
from typing import List
import TTS.api
import TTS.utils.manage as manage
import torch
from pydub import AudioSegment
import gradio as gr
import config
try:
import spaces
USING_SPACES = True
except ImportError:
USING_SPACES = False
def gpu_decorator(func):
if USING_SPACES:
return spaces.GPU(func)
else:
return func
device = "cuda" if torch.cuda.is_available() else "cpu"
def ask_tos_patch(self, output_path):
print("Automatically accepting the terms of service.")
return True
manage.ModelManager.ask_tos = ask_tos_patch
tts = TTS.api.TTS()
models = {}
for id, model in config.models.items():
tts.download_model_by_name(model)
models[id] = TTS.api.TTS(model).to(device)
@gpu_decorator
def synthesize_tts(
text: str = 'Hello, World!',
speaker_wavs: List[gr.File] = None,
speaker_idx: str = 'Ana Florence',
language: str = 'ja',
temperature: float = 0.65,
top_k: int = 50,
top_p: float = 0.8,
speed: float = 1.0,
enable_text_splitting: bool = True,
):
temp_files = []
try:
if speaker_wavs:
for speaker_wav in speaker_wavs:
with open(speaker_wav.name, "rb") as f:
speaker_wav_bytes = f.read()
try:
audio = AudioSegment.from_file(io.BytesIO(speaker_wav_bytes))
wav_buffer = io.BytesIO()
audio.export(wav_buffer, format="wav")
wav_buffer.seek(0)
except Exception as e:
return f"Error processing audio file: {e}"
temp_wav_file = tempfile.NamedTemporaryFile(suffix=".wav", delete=False)
temp_wav_file.write(wav_buffer.read())
temp_wav_file.close()
temp_files.append(temp_wav_file.name)
output_buffer = io.BytesIO()
if temp_files:
models['multi'].tts_to_file(
text=text,
speaker_wav=temp_files,
language=language,
file_path=output_buffer,
temperature=temperature,
top_k=top_k,
top_p=top_p,
speed=speed,
enable_text_splitting=enable_text_splitting
)
else:
models['multi'].tts_to_file(
text=text,
speaker=speaker_idx,
language=language,
file_path=output_buffer,
temperature=temperature,
top_k=top_k,
top_p=top_p,
speed=speed,
enable_text_splitting=enable_text_splitting
)
output_buffer.seek(0)
return output_buffer.read()
finally:
for temp_file in temp_files:
if isinstance(temp_file, str) and os.path.exists(temp_file):
os.remove(temp_file)
inputs = [
gr.Textbox(value="Hello, World!", label="Text to Synthesize"),
gr.Audio(sources=['upload', 'microphone'], label="Voice Clone(optional)", type="filepath"),
gr.Dropdown(
choices=[
"Claribel Dervla", "Daisy Studious", "Gracie Wise", "Tammie Ema", "Alison Dietlinde", "Ana Florence",
"Annmarie Nele", "Asya Anara", "Brenda Stern", "Gitta Nikolina", "Henriette Usha", "Sofia Hellen",
"Tammy Grit", "Tanja Adelina", "Vjollca Johnnie", "Andrew Chipper", "Badr Odhiambo", "Dionisio Schuyler",
"Royston Min", "Viktor Eka", "Abrahan Mack", "Adde Michal", "Baldur Sanjin", "Craig Gutsy",
"Damien Black", "Gilberto Mathias", "Ilkin Urbano", "Kazuhiko Atallah", "Ludvig Milivoj", "Suad Qasim",
"Torcull Diarmuid", "Viktor Menelaos", "Zacharie Aimilios", "Nova Hogarth", "Maja Ruoho", "Uta Obando",
"Lidiya Szekeres", "Chandra MacFarland", "Szofi Granger", "Camilla Holmström", "Lilya Stainthorpe",
"Zofija Kendrick", "Narelle Moon", "Barbora MacLean", "Alexandra Hisakawa", "Alma María", "Rosemary Okafor",
"Ige Behringer", "Filip Traverse", "Damjan Chapman", "Wulf Carlevaro", "Aaron Dreschner", "Kumar Dahl",
"Eugenio Mataracı", "Ferran Simen", "Xavier Hayasaka", "Luis Moray", "Marcos Rudaski"
],
value="Ana Florence",
label="Speaker Index"
),
gr.Dropdown(
choices=["en", "es", "fr", "de", "it", "pt", "pl", "tr", "ru", "nl", "cs", "ar", "zh", "ja", "hu", "ko"],
value="en",
label="Language"
),
gr.Slider(0, 2, value=1, step=0.01, label="Temperature"),
gr.Slider(1, 100, value=50, step=1, label="Top-K"),
gr.Slider(0, 1, value=1, step=0.01, label="Top-P"),
gr.Slider(0.5, 2, value=1.0, step=0.01, label="Speed"),
gr.Checkbox(value=True, label="Enable Text Splitting")
]
outputs = gr.Audio(label="Generated Speech")
gr.Interface(
fn=synthesize_tts,
inputs=inputs,
outputs=outputs,
title="Text-to-Speech Synthesis with Gradio"
).launch()