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import gradio as gr | |
import numpy as np | |
from utils import load_model, normalize_text | |
import time | |
vits = load_model() | |
def text_to_speech(text): | |
""" Text to speech | |
""" | |
text = normalize_text(text) | |
text_inputs = np.asarray( | |
vits.tokenizer.text_to_ids(text), | |
dtype=np.int64, | |
)[None, :] | |
start = time.perf_counter() | |
audio = vits.inference_onnx(text_inputs) | |
end = time.perf_counter() | |
inference_time = end - start | |
audio_length = audio.shape[1] / vits.config.audio.sample_rate | |
print('Inference time: {}'.format(inference_time)) | |
print('Real time factor: {}'.format(inference_time / audio_length)) | |
return 16000, audio[0] | |
gr.Interface( | |
fn=text_to_speech, | |
inputs="text", | |
outputs="audio", | |
theme="default", | |
).launch(debug=False) | |