Use VITS and Opencpop to develop singing voice synthesis; Maybe it will VISinger.

Related tags

Deep Learning VITS_Singing
Overview

Init

Use VITS and Opencpop to develop singing voice synthesis; Maybe it will VISinger.

本项目基于

https://github.com/jaywalnut310/vits
https://github.com/SJTMusicTeam/Muskits/
https://wenet.org.cn/opencpop/ 歌声数据

使用muskit数据预处理，获得初步数据

cd egs/opencpop/svs1/
./local/data.sh

VISinger_data
--lable
--midi_dump
--wav_dump

采样率转换

python wave_16k.py
--wav_dump
--wav_dump_16k

使用muskit将数据处理成vits的格式

1, 将lable进行拆分
python muskit/data_label_single.py

label_dump,midi_dump,wav_dump:一个文件一个标注

注意：label和lable的混用（两个单词都是对的）

VISinger_data
--label_dump
--midi_dump
--wav_dump
--wav_dump_16k

2, 将label和midi处理为frame对应的发音单元和音符（基音）
python muskit/data_format_vits.py
VISinger_data
--label_vits
--label_dump
--midi_dump
--wav_dump
--wav_dump_16k

3, 生成VITS需要的files，并分割为train和dev，test不需要（可以手动设计）
python muskit/data_format_vits.py

vits_file.txt 中的内容格式：wave path|label path|pitch path;

cp vits_file.txt VISinger/filelists/
cd VISinger/

python preprocess.py 分割为train和dev

VITS训练

cd VISinger
CUDA_VISIBLE_DEVICES=0 python train.py -c configs/singing_base.json -m singing_base 2>exit_error.log;cat exit_error.log
python vsinging_infer.py

使用16K节约内存，方便模型修改

编辑midi，然后测试

cd ../;python muskit/infer_midi.py;cd -;python vsinging_edit.py

LOSS值 MEL谱

样例音频

vits_singing_样例.wav

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Comments
  • couple of questions

    couple of questions

    Hello how are you ! very cool stuff you have here ,I can clearly see you love singing voice synthesis (SVS) from your forks and repos !! i wanted to ask is that a fully working Visingerr or is it a try from you to make it to sing , like can it be tested on a custom English data and have like results the same as or near the demo in the paper. Also do you have like other samples i can hear , i know that you tested it on opencpop that has almost 5.2 hours of singing data , and also in the paper they trained Visingerr for 600k iterations right ? how many iterations did you achieve on the opencpop to get the result linked below (vits_singing_样例.wav). to be honest i thought vits is data hungry like tacotron2 or fastspeech (aka needs a lot of data to get great results) , that opencpop result of your is so impressive for 5.2 hours data , i also wonder if you lowered the sample rate of opencpop from 44.1 KHz to 22KHz as i heard 44.1 KHz takes alot of time to train x10 the time needed.

    迫不及待地想知道你的消息 :)

    opened by dutchsing009 5
  • 问题

    问题

    python prepare/data_vits.py 输出 1,../VISinger_data/label_vits/XXX._label.npy|XXX_score.npy|XXX_pitch.npy|XXX_slurs.npy 2,filelists/vits_file.txt 内容格式：wave path|label path|score path|pitch path|slurs path;

    请问1 2这两步是怎么操作？

    opened by baipeng0110 3
  • 训练结果

    训练结果

    目前模型缺乏时长预测模型和基音预测模型； 训练语料中的句子修改歌词的效果；

    原歌词：雨淋湿了天空灰得更讲究

    https://user-images.githubusercontent.com/16432329/164953151-4c2513cb-f336-416b-8f04-604f13e63368.MP4

    修改歌词：你闹够了没有让我更难受

    https://user-images.githubusercontent.com/16432329/164953155-16c72670-cc89-40bc-99fe-42781c9dcdc0.MP4

    help wanted 
    opened by MaxMax2016 0
  • About release models and VISinger

    About release models and VISinger

    Hi

    This is a fantastic project that I have ever seen.

    Could you please share the released model? As on the inference step, it is said that "using the released model"

    Also, is there any plan to implement the VISinger model?

    Thank you!

    opened by shiyanpei0826 1
Owner
AmorTX
Speech
AmorTX
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