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添加数据预处理环节的音频降噪功能，提高模型性能

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添加数据预处理环节的音频降噪功能，提高模型性能
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刘悦 2024-01-28 15:50:52 +08:00 committed by GitHub
parent 6e224464c8
commit 64cdc97277
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1 changed files with 16 additions and 1 deletions
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webui.py
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@ -5,6 +5,8 @@ import json,yaml,warnings,torch
import platform import platform
import psutil import psutil
import signal import signal
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
warnings.filterwarnings("ignore") warnings.filterwarnings("ignore")
torch.manual_seed(233333) torch.manual_seed(233333)
@ -210,6 +212,17 @@ def close_asr():
p_asr=None p_asr=None
return "已终止ASR进程",{"__type__":"update","visible":True},{"__type__":"update","visible":False} return "已终止ASR进程",{"__type__":"update","visible":True},{"__type__":"update","visible":False}
# 音频降噪
def reset_tts_wav(audio):
ans = pipeline(
Tasks.acoustic_noise_suppression,
model='damo/speech_frcrn_ans_cirm_16k')
ans(audio,output_path='./output_ins.wav')
return "./output_ins.wav"
p_train_SoVITS=None p_train_SoVITS=None
def open1Ba(batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D): def open1Ba(batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,save_every_epoch,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D):
global p_train_SoVITS global p_train_SoVITS
@ -634,7 +647,8 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
gr.Markdown(value=i18n("0b-语音切分工具")) gr.Markdown(value=i18n("0b-语音切分工具"))
with gr.Row(): with gr.Row():
with gr.Row(): with gr.Row():
slice_inp_path=gr.Textbox(label=i18n("音频自动切分输入路径，可文件可文件夹"),value="") #slice_inp_path=gr.Textbox(label=i18n("音频自动切分输入路径，可文件可文件夹"),value="")
slice_inp_path = gr.Audio(label=i18n("请上传克隆对象音频"), type="filepath")
slice_opt_root=gr.Textbox(label=i18n("切分后的子音频的输出根目录"),value="output/slicer_opt") slice_opt_root=gr.Textbox(label=i18n("切分后的子音频的输出根目录"),value="output/slicer_opt")
threshold=gr.Textbox(label=i18n("threshold:音量小于这个值视作静音的备选切割点"),value="-34") threshold=gr.Textbox(label=i18n("threshold:音量小于这个值视作静音的备选切割点"),value="-34")
min_length=gr.Textbox(label=i18n("min_length:每段最小多长，如果第一段太短一直和后面段连起来直到超过这个值"),value="4000") min_length=gr.Textbox(label=i18n("min_length:每段最小多长，如果第一段太短一直和后面段连起来直到超过这个值"),value="4000")
@ -648,6 +662,7 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
alpha=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("alpha_mix:混多少比例归一化后音频进来"),value=0.25,interactive=True) alpha=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("alpha_mix:混多少比例归一化后音频进来"),value=0.25,interactive=True)
n_process=gr.Slider(minimum=1,maximum=n_cpu,step=1,label=i18n("切割使用的进程数"),value=4,interactive=True) n_process=gr.Slider(minimum=1,maximum=n_cpu,step=1,label=i18n("切割使用的进程数"),value=4,interactive=True)
slicer_info = gr.Textbox(label=i18n("语音切割进程输出信息")) slicer_info = gr.Textbox(label=i18n("语音切割进程输出信息"))
reset_inp_button.click(reset_tts_wav,[slice_inp_path],[slice_inp_path])
gr.Markdown(value=i18n("0c-中文批量离线ASR工具")) gr.Markdown(value=i18n("0c-中文批量离线ASR工具"))
with gr.Row(): with gr.Row():
open_asr_button = gr.Button(i18n("开启离线批量ASR"), variant="primary",visible=True) open_asr_button = gr.Button(i18n("开启离线批量ASR"), variant="primary",visible=True)