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fix params in paper
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azraelkuan committed Aug 31, 2021
1 parent df77c9a commit f784d5f
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7 changes: 1 addition & 6 deletions README.md
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Expand Up @@ -129,19 +129,14 @@ python inference.py -p CHECKPOINT_PATH -i INPUT_MEL_PATH

You can download checkpoint of pre-trained model from **[Google Drive](https://drive.google.com/file/d/1pZV5q59FfIV4sUp9JobXAUjK4-Y-x2q_/view?usp=sharing)**.
The model was trained on LibriTTS train-clean-360 split.
> please use `config/legacy.yaml` to load the pre-trained model. for new version, we have fixed the problem of mismatched params.

## Results

See audio samples at https://mindslab-ai.github.io/univnet/

<img src="docs/loss.png" width="100%">

## Note

This code is an unofficial implementation, there may be some differences from the original paper.

- Our UnivNet generator has smaller number of parameters (c32: 5.11M, c16: 1.42M) than the paper (c32: 14.89M, c16: 4.00M). So far, we have not encountered any issues from using a smaller model size. If run into any problem, please report it as an issue.

## Implementation Authors

Implementation authors are:
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1 change: 1 addition & 0 deletions config/default.yaml
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Expand Up @@ -33,6 +33,7 @@ gen:
dilations: [1, 3, 9, 27]
strides: [8, 8, 4]
lReLU_slope: 0.2
kpnet_conv_size: 3
#############################
mpd:
periods: [2,3,5,7,11]
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4 changes: 3 additions & 1 deletion model/generator.py
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Expand Up @@ -14,6 +14,7 @@ def __init__(self, hp):
self.noise_dim = hp.gen.noise_dim
self.hop_length = hp.audio.hop_length
channel_size = hp.gen.channel_size
kpnet_conv_size = hp.gen.kpnet_conv_size

self.res_stack = nn.ModuleList()
hop_length = 1
Expand All @@ -26,7 +27,8 @@ def __init__(self, hp):
stride=stride,
dilations=hp.gen.dilations,
lReLU_slope=hp.gen.lReLU_slope,
cond_hop_length=hop_length
cond_hop_length=hop_length,
kpnet_conv_size=kpnet_conv_size
)
)

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2 changes: 1 addition & 1 deletion model/lvcnet.py
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Expand Up @@ -107,7 +107,7 @@ def __init__(
conv_kernel_size=3,
cond_hop_length=256,
kpnet_hidden_channels=64,
kpnet_conv_size=1,
kpnet_conv_size=3,
kpnet_dropout=0.0,
):
super().__init__()
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