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from models import SynthesizerTrn
from vits_pinyin import VITS_PinYin
from text import cleaned_text_to_sequence
from text.symbols import symbols
import gradio as gr
import utils
import torch
import argparse
import os
import re
import logging
logging.getLogger('numba').setLevel(logging.WARNING)
limitation = os.getenv("SYSTEM") == "spaces"
def create_calback(net_g: SynthesizerTrn, tts_front: VITS_PinYin):
def tts_calback(text, dur_scale):
if limitation:
text_len = len(re.sub("\[([A-Z]{2})\]", "", text))
max_len = 150
if text_len > max_len:
return "Error: Text is too long", None
phonemes, char_embeds = tts_front.chinese_to_phonemes(text)
input_ids = cleaned_text_to_sequence(phonemes)
with torch.no_grad():
x_tst = torch.LongTensor(input_ids).unsqueeze(0).to(device)
x_tst_lengths = torch.LongTensor([len(input_ids)]).to(device)
x_tst_prosody = torch.FloatTensor(
char_embeds).unsqueeze(0).to(device)
audio = net_g.infer(x_tst, x_tst_lengths, x_tst_prosody, noise_scale=0.5,
length_scale=dur_scale)[0][0, 0].data.cpu().float().numpy()
del x_tst, x_tst_lengths, x_tst_prosody
return "Success", (16000, audio)
return tts_calback
example = [['这星球，天天有五十亿人，在错过，多幸运，有你一起看星星，在争宠，这一刻不再问为什么不再去猜测人和人，心和心，有什么不同。', 1],
['当你说，太聪明，往往还是，会寂寞，我笑着，倾听孤单终结后的静寞，看月亮像夜空的瞳孔，静静凝视你我，和我们闹嚷的星球。', 1],
['床前明月光，疑是地上霜，举头望明月，低头思故乡。', 1],]
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--share", action="store_true",
default=False, help="share gradio app")
args = parser.parse_args()
device = torch.device("cpu")
# pinyin
tts_front = VITS_PinYin("./bert", device)
# config
hps = utils.get_hparams_from_file("./configs/bert_vits.json")
# model
net_g = SynthesizerTrn(
len(symbols),
hps.data.filter_length // 2 + 1,
hps.train.segment_size // hps.data.hop_length,
**hps.model)
model_path = "vits_bert_model.pth"
utils.load_model(model_path, net_g)
net_g.eval()
net_g.to(device)
tts_calback = create_calback(net_g, tts_front)
app = gr.Blocks()
with app:
gr.Markdown("# Mandarin-TTS\n\n"
)
with gr.Tabs():
with gr.TabItem("TTS"):
with gr.Row():
with gr.Column():
textbox = gr.TextArea(label="Text",
placeholder="Type your sentence here (Maximum 150 words)",
value="中文语音合成", elem_id=f"tts-input")
duration_slider = gr.Slider(minimum=0.1, maximum=5, value=1, step=0.1,
label='速度 Speed')
with gr.Column():
text_output = gr.Textbox(label="Message")
audio_output = gr.Audio(
label="Output Audio", elem_id="tts-audio")
btn = gr.Button("Generate!")
btn.click(tts_calback,
inputs=[textbox, duration_slider],
outputs=[text_output, audio_output])
gr.Examples(
examples=example,
inputs=[textbox, duration_slider],
outputs=[text_output, audio_output],
fn=tts_calback
)
app.queue(concurrency_count=3).launch(show_api=False, share=args.share)
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