The majority of VocBench is licensed under CC-BY-NC, however portions of the project are available under separate license terms: Wavenet, ParallelWaveGAN, and flops counter are licensed under the MIT license; diffwave is licensed under the Apache 2.0 license; WaveGrad is licensed under the BSD-3 license.
Hi,
In your paper, you train and compare different models on various metrics. Are you planning on releasing the model weights you obtained as pretrained models?
Regards,
This is pull request was created automatically because we noticed your project was missing a Code of Conduct file.
Code of Conduct files facilitate respectful and constructive communities by establishing expected behaviors for project contributors.
This PR was crafted with love by Facebook's Open Source Team.
CLA SignedThis is pull request was created automatically because we noticed your project was missing a Contributing file.
CONTRIBUTING files explain how a developer can contribute to the project - which you should actively encourage.
This PR was crafted with love by Facebook's Open Source Team.
CLA SignedHello,
Thank you for your great work and for making your code publicly available!
I'm wondering why the number of iterations for Parallel WaveGAN is set to 4M. https://github.com/facebookresearch/vocoder-benchmark/blob/2d30cf5885ea53c651db47c421c4c44cddc0c142/config/parallel_wavegan.yaml#L84 This is much larger than that of kan-bayashi. Do you have a reason for this? I'd appreciate it if you could let me know.
Thanks.
Thanks for making this benchmarking framework. I see that currently there's no flow-based vocoder model. It would be interesting to see how diffusion-based models compare to flow-based models cuz they're kind of similar, so I add an implementation of waveflow. The implementation is copied from my constant memory waveglow repo.
CLA SignedImage Quality Evaluation Metrics Implementation of some common full reference image quality metrics. The repo is built based on full reference image q
Heterogeneous Graph Benchmark Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks. Roadmap We organize our repo by task, and on
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their
The Neural Process Family This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CN
Character-Input Create a program that asks the user to enter their name and thei
Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built
Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built
FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca
The first comprehensive Robustness investigation benchmark on large-scale dataset ImageNet regarding ARchitecture design and Training techniques towards diverse noises.
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking We revisit and address issues with Oxford 5k and Paris 6k image retrieval benchm
ModelNet-C Code for the paper "Benchmarking and Analyzing Point Cloud Classification under Corruptions". For the latest updates, see: sites.google.com
Speech Super-resolution Evaluation and Benchmarking What this repo do: A toolbox for the evaluation of speech super-resolution algorithms. Unify the e
Map Metrics for Trajectory Quality Map metrics toolkit provides a set of metrics to quantitatively evaluate trajectory quality via estimating consiste
Don’t be Contradicted with Anything!CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System This repository contains the PyTorch im
PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System
Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery
B-Pref Official codebase for B-Pref: Benchmarking Preference-BasedReinforcement Learning contains scripts to reproduce experiments. Install conda env
Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery
Benchmark for Tuning Accuracy and Efficiency Overview The benchmark includes our
10 Jan 1, 2023
176 Dec 17, 2022
8 May 22, 2022
892 Dec 28, 2022
0 Feb 6, 2022
6.2k Jan 1, 2023
268 Jan 1, 2023
132 Dec 23, 2022
188 Dec 17, 2022
45 Dec 28, 2022
84 Dec 20, 2022
31 Oct 28, 2022
25 Sep 6, 2022
3 Oct 14, 2022
48 Dec 20, 2022
656 Dec 29, 2022
31 Oct 7, 2022