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Hi,
I want to ask whether your code about training Mel-GAN vocoder is support multiple GPUs? In you paper, you use one single GPU training about 14 days. So I want to ask you whether we can use mu…
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## 論文タイトル(原文まま)
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
## 一言でいうと
HiFi-GANは、効率的かつ高忠実度な音声合成を実現するために設計された生成対向ネットワーク(GAN)であり、最新のモデルと比較して高い品質と高速な合成を…
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Dear authors,
Maybe it seems novice but when I tried train.py with my dataset (and also LJ dataset), I found the y variable is having only one frame (1, 513). Any idea why this happens? My audios a…
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step 1 torch2onnx:
```python3
#!/ssd4/exec/huangps/anaconda3/envs/melgan/bin/python
import torch
import torchvision
import numpy as np
from model.generator import Generator
from utils.hparams…
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Hello, thanks for your nice implementation of mel-gan.
I guess mel-gan can be used as the universal vocoder, and I thought there were a mention about multi-speaker training scheme in the original p…
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I'd like to train hifi-gan on a custom dataset with its own set of wav files. For this I need to generate the corresponding mel spectrograms, which the readme says can be done using Tacotron2 although…
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Hi
Thanks for this great implementation.
I trained Tacotron and used WaveRNN as vocoder and result was good. Now I want to use HiFi-GAN as vocoder so I cloned this project and run it with mel-spectr…
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I trained a model using hifi-gan and VCTK and testing on the wav files it looks good
However, when I try to use the model on mel-spectrograms generated by TensorflowTTS/tacotron2 all I get is noise…
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Can you provide me with the code to convert wav to wav to do it the indirect way?
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getting error - **RuntimeError: stack expects each tensor to be equal size, but got [8192] at entry 0 and [8129] at entry 12**
Do anyone have a solution to do it ?