V1.12

As many users have already tested the current version, it should be stable.
该版本已经过大量用户测试, 他应该已经稳定了.

We will modify the dataset structure and add data augmentation in the next version (which will lead to many changes).
我们将在下个版本优化数据集结构和添加数据增强 (可能还有完善 DiffSinger), 这有可能导致程序爆炸.

除此之外, 我们放出了一个测试版声码器, 配置文件和 OpenVPI NSF-HiFiGAN 一致. 它再高频和低频有更好的表现 (起码不会破音了).
Besides that, we released a beta vocoder, which has an identical config as OpenVPI's NSF-HiFiGAN. It has a higher performance on both high and low notes.

使用方法: 下载 nsf_hifigan-beta-v2-epoch-434.zip 解压到 checkpoints
How to use: Download and decompress nsf_hifigan-beta-v2-epoch-434.zip to checkpoints

注: 该测试声码器在 M4Singer 和 OpenCpop 上训练了大约三天 (双路 3090). 我们会在更优质的数据集上训练, 并发布一个正式版.
Note: This beta VOCODER was trained on M4Singer and OpenCpop for about 3 days; we will release a vocoder trained on in-house data later.

03-01 更新:
03-01 Update:

• 我们把模型多训练了一天, 并且提供了 onnx 导出文件.
• We trained the model for one extra day and provided the ONNX model.
• 为了更方便用户使用, 我们还增加了 OpenUTAU vocoder: nsf_hifigan-beta-v2-epoch-434.dsvocoder.
• For convenience, we also attached an OpenUTAU vocoder: nsf_hifigan-beta-v2-epoch-434.dsvocoder.

该声码器在 Attribution-NonCommercial-ShareAlike 4.0 International 协议下发布.
Pretrained vocoders are released under the Attribution-NonCommercial-ShareAlike 4.0 International license.

03-03 更新:
03-03 Update:

• 我们将 ContentVec 中的 content-vec-best-legacy-500.pt 加入了附件, 方便用户下载.
• For your convenience, we added ContentVec's content-vec-best-legacy-500.pt.