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

Related tags

Deep LearningVITS_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

You might also like...
In this project, we develop a face recognize platform based on MTCNN object-detection netcwork and FaceNet self-supervised network.
In this project, we develop a face recognize platform based on MTCNN object-detection netcwork and FaceNet self-supervised network.

模式识别大作业——人脸检测与识别平台 本项目是一个简易的人脸检测识别平台，提供了人脸信息录入和人脸识别的功能。前端采用 html+css+js，后端采用 pytorch，

Xuhua Huang 5 Aug 2, 2022
Official codebase used to develop Vision Transformer, MLP-Mixer, LiT and more.

Big Vision This codebase is designed for training large-scale vision models on Cloud TPU VMs. It is based on Jax/Flax libraries, and uses tf.data and

Google Research 701 Jan 3, 2023
Use MATLAB to simulate the signal and extract features. Use PyTorch to build and train deep network to do spectrum sensing.

Deep-Learning-based-Spectrum-Sensing Use MATLAB to simulate the signal and extract features. Use PyTorch to build and train deep network to do spectru

null 10 Dec 14, 2022
Transfer style api - An API to use with Tranfer Style App, where you can use two image and transfer the style

Transfer Style API It's an API to use with Tranfer Style App, where you can use

Brian Alejandro 1 Feb 13, 2022
Voice of Pajlada with model and weights.

Pajlada TTS Stripped down version of ForwardTacotron (https://github.com/as-ideas/ForwardTacotron) with pretrained weights for Pajlada's (https://gith

null 6 Sep 3, 2021
A voice recognition assistant similar to amazon alexa, siri and google assistant.
A voice recognition assistant similar to amazon alexa, siri and google assistant.

kenyan-Siri Build an Artificial Assistant Full tutorial (video) To watch the tutorial, click on the image below Installation For windows users (run th

Alison Parker 3 Aug 19, 2022
An implementation of
An implementation of "Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport"

Optex An implementation of Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport for TU Delft CS4240. You c

Hans Brouwer 33 Jan 5, 2023
this is a lite easy to use virtual keyboard project for anyone to use
this is a lite easy to use virtual keyboard project for anyone to use

virtual_Keyboard this is a lite easy to use virtual keyboard project for anyone to use motivation I made this for this year's recruitment for RobEn AA

Mohamed Emad 3 Oct 23, 2021
A collection of easy-to-use, ready-to-use, interesting deep neural network models
A collection of easy-to-use, ready-to-use, interesting deep neural network models

Interesting and reproducible research works should be conserved. This repository wraps a collection of deep neural network models into a simple and un

Aria Ghora Prabono 16 Jun 16, 2022
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
GitHub Repository
Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.

Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N

HUAWEI Noah's Ark Lab 2.6k Jan 01, 2023
An implementation of EWC with PyTorch

EWC.pytorch An implementation of Elastic Weight Consolidation (EWC), proposed in James Kirkpatrick et al. Overcoming catastrophic forgetting in neural

Ryuichiro Hataya 166 Dec 22, 2022
A high-level Python library for Quantum Natural Language Processing

lambeq About lambeq is a toolkit for quantum natural language processing (QNLP). Documentation: https://cqcl.github.io/lambeq/ Getting started Prerequ

Cambridge Quantum 315 Jan 01, 2023
Categorizing comments on YouTube into different categories.

Youtube Comments Categorization This repo is for categorizing comments on a youtube video into different categories. negative (grievances, complaints,

Rhitik 5 Nov 26, 2022
A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval

CLIP4CMR A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval The original data and pre-calculate

24 Dec 26, 2022
Convolutional Neural Network to detect deforestation in the Amazon Rainforest

Convolutional Neural Network to detect deforestation in the Amazon Rainforest This project is part of my final work as an Aerospace Engineering studen

5 Feb 17, 2022
Keras attention models including botnet,CoaT,CoAtNet,CMT,cotnet,halonet,resnest,resnext,resnetd,volo,mlp-mixer,resmlp,gmlp,levit

Keras_cv_attention_models Keras_cv_attention_models Usage Basic Usage Layers Model surgery AotNet ResNetD ResNeXt ResNetQ BotNet VOLO ResNeSt HaloNet

319 Dec 28, 2022
Keeper for Ricochet Protocol, implemented with Apache Airflow

Ricochet Keeper This repository contains Apache Airflow DAGs for executing keeper operations for Ricochet Exchange. Usage You will need to run this us

Ricochet Exchange 5 May 24, 2022
Trax — Deep Learning with Clear Code and Speed

Trax — Deep Learning with Clear Code and Speed Trax is an end-to-end library for deep learning that focuses on clear code and speed. It is actively us

Google 7.3k Dec 26, 2022
Semi-supervised Transfer Learning for Image Rain Removal. In CVPR 2019.

Semi-supervised Transfer Learning for Image Rain Removal This package contains the Python implementation of "Semi-supervised Transfer Learning for Ima

Wei Wei 59 Dec 26, 2022
Implicit Deep Adaptive Design (iDAD)

Implicit Deep Adaptive Design (iDAD) This code supports the NeurIPS paper 'Implicit Deep Adaptive Design: Policy-Based Experimental Design without Lik

Desi 12 Aug 14, 2022
A PyTorch re-implementation of Neural Radiance Fields

nerf-pytorch A PyTorch re-implementation Project | Video | Paper NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis Ben Mildenhall

Krishna Murthy 709 Jan 09, 2023
Learning Generative Models of Textured 3D Meshes from Real-World Images, ICCV 2021

Learning Generative Models of Textured 3D Meshes from Real-World Images This is the reference implementation of "Learning Generative Models of Texture

Dario Pavllo 115 Jan 07, 2023
Signals-backend - A suite of card games written in Python

Card game A suite of card games written in the Python language. Features coming

1 Feb 15, 2022
A fast model to compute optical flow between two input images.

DCVNet: Dilated Cost Volumes for Fast Optical Flow This repository contains our implementation of the paper: @InProceedings{jiang2021dcvnet, title={

Huaizu Jiang 8 Sep 27, 2021
Pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"

About this repository This repo contains an Pytorch implementation for the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Netwo

wxDai 7 Oct 14, 2022
Heterogeneous Deep Graph Infomax

Heterogeneous-Deep-Graph-Infomax Parameter Setting: HDGI-A: Node-level dimension: 16 Attention head: 4 Semantic-level attention vector: 8 learning rat

52 Oct 31, 2022
Code base for reproducing results of I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics. NeurIPS (2021)

Learning to Execute (L2E) Official code base for completely reproducing all results reported in I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learnin

3 May 18, 2022
TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations

TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations Requirements python 3.6 torch 1.9 numpy 1.19 Quick Start The experimen

DMIRLAB 4 Oct 16, 2022
NeuroGen: activation optimized image synthesis for discovery neuroscience

NeuroGen: activation optimized image synthesis for discovery neuroscience NeuroGen is a framework for synthesizing images that control brain activatio

3 Aug 17, 2022