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License: Apache License 2.0
LVCNet: Efficient Condition-Dependent Modeling Network for Waveform Generation
License: Apache License 2.0
hello @zceng, thanks for your contribution in LVCNet.
I follow your default experiment's setting about training LJSpeech. Including sampling rate = 22050, batch_size = 8 and so on. But I have a poor synthesis although training reached checkpoint-180000.
real:
generate:
wavs zip:
0100_wavs.zip
Is it because not enough training? or other reasons?
Looking forward to your reply.
Thanks.
LVCnet他没有nsf哈斯会有hifigan一样的问题 (容易断音)
但是lvc 不是直接上采样mel 还有方法可以添加nsf吗?
nsf 就是下面链接的那种
https://github.com/vtuber-plan/NSF-HiFiGAN
https://nii-yamagishilab.github.io/samples-nsf/
How may days needed for training? And what is the batch_size?
In MELGAN, there is not input noise as x. So
首先,感谢您在声码器上做的努力
我想问一下,推理速度上有与原始LPCNet做过对比吗
wavs: 16k hop_size=200
when i set:
generator_params:
in_channels: 1 # Number of input channels.
out_channels: 1 # Number of output channels.
inner_channels: 8
cond_channels: 80
cond_hop_length: 200 #256
lvc_block_nums: 3
lvc_layers_each_block: 10
lvc_kernel_size: 3
kpnet_hidden_channels: 64
kpnet_conv_size: 1
dropout: 0.0
use_weight_norm: true # Whether to use weight norm.
When my data is 16k, hop_size=200, how should the parameters be set? thank you
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