deepjavalibrary / deepjavalibrary/djl

Manual porting of QPPWG(Quasi Periodic Parrallel Wave-Gan)

Open
#338 8 comments 0 reactions 0 assignees View on GitHub
enhancement
Dominant language
Java
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4.9k
Forks
759
Avg merge
19h 26m
Merged PRs (30d)
17

Description

## Description
(A clear and concise description of what the feature is.)
A api that can let user uses QPPWG not in a very user friendly sense.
This is just the start.I also do not have enough experience in this repo.

### Will this change the current api? How?
Proably no,just adding stuff in or can even seperate packaging.
The original api is also well built for extending should h=not have huge problem.

### Who will benefit from this enhancement?
everyone who uses it.lol

## References
- list reference and related literature
[Quasi-Periodic Parallel WaveGAN Vocoder: A Non-autoregressive Pitch-
dependent Dilated Convolution Model for Parametric Speech Generation](https://arxiv.org/abs/2007.12955)
- list known implementations
[original python pytorch implementation in github](https://github.com/bigpon/QPPWG)

Extra notes and questions.
I am just a 19 years old jobless human and currently did not take any college etc..
So please bear with my stupidity or lack of experience in various things.

I think this will need two phase.
1)Making various parts.(Why?Because it introduces few new parts that is custom and implemented in pure python..)
2)Making sure it will works.(Yes,I am new and do not have confident in setting it up and testing it.)

Of course a more experienced contributor can port it.I just simply need to use it.

Contributor guide

Open the contributing guide

Research direction

Start by reading the linked original Python PyTorch implementation and the repository's existing API before defining the port's scope. The work is done when QPPWG is available through a user-friendly API or separate package and the implementation can be set up and tested successfully.

Written by the indexing model from the issue text.

Assessment

Tech stack
java, python, pytorch
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
15/100

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