Results 8 issues of yqzhishen

I noticed that the supported datasets of this repository have different audio sample rate. Is the output sample rate of FastDiff vocoder bound to its training data, or does it...

Are there any experiments done to evaluate the performance of FastDiff on singing voice datasets?

Hello and thank you for your great work. However, I tried MIDI SVS of DiffSinger and found that there might be a conceptual mistake in the phoneme duration inference logic,...

enhancement
must-read

The following checks are performed between DiffSinger vocoder and acoustic model: - `sample_rate`, `hop_size`, `num_mel_bins`, `mel_fmin`, `mel_fmax` must be equal - `mel_scale` must be equal and must be `slaney` or...

Some batch edits like DiffSinger autopitch may execute really slowly and block the UI. This PR supports running batch edits asynchronously, with a dialog showing progress of the running batch...

Fixes a tiny mistake in the error message.

**Describe the bug** ONNX Simplifier fails to simplify models with optional types. The following minimum demo: ```python from typing import Optional import onnx import onnxsim import torch class MyModule(torch.nn.Module): def...

The former iSTFT code has a bug which will produce wrong results when batch_size > 1: ```python coffidx = th.where(coff > 1e-8) outputs[coffidx] = outputs[coffidx]/(coff[coffidx]) ``` When you use `torch.where(condition)`,...