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import re
import time
import gradio as gr
import torch
import commons
import utils
from models import SynthesizerTrn
from text import text_to_sequence
config_json = "configs//multi.json"
pth_path = "model//G=728.pth"
lan = ["中文", "日文", "英文", "德语", "克罗地亚语"]
def get_text(text, hps, cleaned=False):
if cleaned:
text_norm = text_to_sequence(text, hps.symbols, [])
else:
text_norm = text_to_sequence(text, hps.symbols, hps.data.text_cleaners)
if hps.data.add_blank:
text_norm = commons.intersperse(text_norm, 0)
text_norm = torch.LongTensor(text_norm)
return text_norm
def get_label(text, label):
if f'[{label}]' in text:
return True, text.replace(f'[{label}]', '')
else:
return False, text
def sle(language, tts_input0):
if language == "中文":
tts_input1 = "[ZH]" + tts_input0.replace('\n', '。') + "[ZH]"
return tts_input1
if language == "英文":
tts_input1 = "[EN]" + tts_input0.replace('\n', '.') + "[EN]"
return tts_input1
elif language == "日文":
tts_input1 = "[JA]" + tts_input0.replace('\n', '。') + "[JA]"
return tts_input1
elif language == "德语":
tts_input1 = "[DE]" + tts_input0.replace('\n', '.') + "[DE]"
return tts_input1
elif language == "克罗地亚语":
tts_input1 = "[CR]" + tts_input0.replace('\n', '.') + "[CR]"
return tts_input1
def load_model(config_json, pth_path):
dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
hps_ms = utils.get_hparams_from_file(f"{config_json}")
n_speakers = hps_ms.data.n_speakers if 'n_speakers' in hps_ms.data.keys() else 0
n_symbols = len(hps_ms.symbols) if 'symbols' in hps_ms.keys() else 0
net_g_ms = SynthesizerTrn(
n_symbols,
hps_ms.data.filter_length // 2 + 1,
hps_ms.train.segment_size // hps_ms.data.hop_length,
n_speakers=n_speakers,
**hps_ms.model).to(dev)
_ = net_g_ms.eval()
_ = utils.load_checkpoint(pth_path, net_g_ms)
return net_g_ms
net_g_ms = load_model(config_json, pth_path)
def infer(language, text, speaker_id, n_scale=0.667, n_scale_w=0.8, l_scale=1):
hps_ms = utils.get_hparams_from_file(f"{config_json}")
stn_tst = get_text(sle(language, text), hps_ms)
speaker_id = int(i_dict[speaker_id])
dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
with torch.no_grad():
x_tst = stn_tst.unsqueeze(0).to(dev)
t1 = time.time()
x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).to(dev)
sid = torch.LongTensor([speaker_id]).to(dev)
audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=n_scale, noise_scale_w=n_scale_w,
length_scale=l_scale)[0][
0, 0].data.cpu().float().numpy()
t2 = time.time()
spending_time = "推理时间：" + str(t2 - t1) + "s"
print(spending_time)
return (hps_ms.data.sampling_rate, audio)
i_dict = {
"ことり(JAP)": 1,
"うみ(JAP)": 0,
"えり(JAP)": 6,
"小文(CHN)": 9,
"小菊(CHN)": 10,
"小标(CHN)": 11,
"Helena(HRV)": 14,
"Erika(DEU)": 19,
"Diana(ENG)": 26,
"Michelle(ENG)": 30,
}
idols = [
"ことり(JAP)",
"うみ(JAP)",
"えり(JAP)",
"小文(CHN)",
"小菊(CHN)",
"小标(CHN)",
"Helena(HRV)",
"Erika(DEU)",
"Diana(ENG)",
"Michelle(ENG)"
]
app = gr.Blocks()
with app:
with gr.Tabs():
with gr.TabItem("幻音文字转语音"):
tts_input1 = gr.TextArea(label="支持英语、日语、德语、中文、克罗地亚语", value="大家好")
language = gr.Dropdown(label="选择语言", choices=lan, value="中文", interactive=True)
para_input1 = gr.Slider(minimum=0.01, maximum=1.0, label="更改噪声比例", value=0.667)
para_input2 = gr.Slider(minimum=0.01, maximum=1.0, label="更改噪声偏差", value=0.8)
para_input3 = gr.Slider(minimum=0.1, maximum=10, label="更改时间比例", value=1)
tts_submit = gr.Button("Generate", variant="primary")
speaker1 = gr.Dropdown(label="选择说话人", choices=idols, value="小文(CHN)", interactive=True)
tts_output2 = gr.Audio(label="Output")
tts_submit.click(infer, [language, tts_input1, speaker1, para_input1, para_input2, para_input3],
[tts_output2])
app.launch()
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