npvcc2016 - Python loader of npVCC2016Corpus

npvcc2016 is a Python package for loader of npVCC2016 non-parallel speech corpus.
For machine learning, corpus/dataset is indispensable - but troublesome - part.
We need portable & flexible loader for streamline development.
npvcc2016 is the one!!

Demo

Python/PyTorch

pip install npvcc2016

from npvcc2016.PyTorch.dataset.waveform import NpVCC2016_wave

dataset = NpVCC2016(train=True, download=True)

for datum in dataset:
    print("Yeah, data is acquired with only two line of code!!")
    print(datum) # (datum, label) tuple provided

npvcc2016 transparently downloads corpus, structures the data and provides standarized datasets.
What you have to do is only instantiating the class!

APIs

Current npvcc2016 support PyTorch.
As interface, PyTorch's Dataset and PyTorch-Lightning's DataModule are provided.
npVCC2016 corpus is speech corpus, so we provide waveform dataset and spectrogram dataset for both interfaces.

• PyTorch
  • (pure PyTorch) dataset
    • waveform: NpVCC2016_wave
    • spectrogram: NpVCC2016_spec
  • PyTorch-Lightning
    • waveform: NpVCC2016_wave_DataModule
    • spectrogram: NpVCC2016_spec_DataModule

Dependency Notes

PyTorch version

PyTorch version: PyTorch v1.6 is working (We checked with v1.6.0).

For dependency resolution, we do NOT explicitly specify the compatible versions.
PyTorch have several distributions for various environment (e.g. compatible CUDA version.)
Unfortunately it make dependency version management complicated for dependency management system.
In our case, the system poetry cannot handle cuda variant string (e.g. torch>=1.6.0 cannot accept 1.6.0+cu101.)
In order to resolve this problem, we use torch==*, it is equal to no version specification.
Setup.py could resolve this problem (e.g. torchaudio's setup.py), but we will not bet our effort to this hacky method.