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import gradio as gr
import time
import torch
import scipy
from espnet2.bin.tts_inference import Text2Speech
from espnet2.utils.types import str_or_none
lang = 'English'
tag = 'kan-bayashi/ljspeech_vits'
vocoder_tag = "none"
text2speech = Text2Speech.from_pretrained(
model_tag=str_or_none(tag),
vocoder_tag=str_or_none(vocoder_tag),
device="cpu",
# Only for Tacotron 2 & Transformer
threshold=0.5,
# Only for Tacotron 2
minlenratio=0.0,
maxlenratio=10.0,
use_att_constraint=False,
backward_window=1,
forward_window=3,
# Only for FastSpeech & FastSpeech2 & VITS
speed_control_alpha=1.0,
# Only for VITS
noise_scale=0.333,
noise_scale_dur=0.333,
)
def inference(text):
with torch.no_grad():
start = time.time()
wav = text2speech(text)["wav"]
scipy.io.wavfile.write("out.wav",text2speech.fs , wav.view(-1).cpu().numpy())
return "out.wav"
title = "TTS"
description = "demo for Anime2Sketch. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2104.05703'>Adversarial Open Domain Adaption for Sketch-to-Photo Synthesis</a> | <a href='https://github.com/Mukosame/Anime2Sketch'>Github Repo</a></p>"
gr.Interface(
inference,
"text",
gr.outputs.Audio(type="file", label="Output"),
title=title,
description=description,
article=article,
enable_queue=True
).launch(debug=True)
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