Dépôts de mpariente

:link: Some useful websites for programmers.

Dernier commit 8 juin 2017

This repo contains the scripts, models and required files for the Interspeech 2020 Deep Noise Suppression (DNS) Challenge. We are open sourcing clean speech and noise files as well. Participants of this challenge will use the scripts from this repo to create data to train their noise suppressors. They will compare their method with our baseline noise suppressor and report the results.

Dernier commit 13 févr. 2020

Implementation for paper "iMetricGAN: Intelligibility Enhancement for Speech-in-Noise using Generative Adversarial Network-based Metric Learning"

Dernier commit 10 avr. 2020

An open source dataset for source separation

Dernier commit 25 mai 2020

First repository

Dernier commit 29 oct. 2018

Dernier commit 5 juin 2020

Ranger - a synergistic optimizer using RAdam (Rectified Adam) and LookAhead in one codebase

Dernier commit 30 mars 2020

A Pure-Python Real-Time Audio Library

Dernier commit 27 juin 2018

A must-read paper for speech separation based on neural networks

Dernier commit 16 mars 2020

A Flexible and Powerful Parameter Server for large-scale machine learning

Dernier commit 31 juil. 2020

simple audio I/O for pytorch

Dernier commit 11 juil. 2019

Build the Linux Kernel and Modules on board the NVIDIA Jetson Nano Developer Kit

Dernier commit 26 nov. 2019

https://github.com/DataTalksClub

Dernier commit 19 janv. 2026

Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼

Dernier commit 15 janv. 2026

🤗 Fast, efficient, open-access datasets and evaluation metrics in PyTorch, TensorFlow, NumPy and Pandas

Dernier commit 4 déc. 2020

Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

Dernier commit 4 sept. 2020

End-to-End Speech Processing Toolkit

Dernier commit 14 août 2020

We'll see what this becomes

Dernier commit 22 mai 2022

Header-only library for using Keras models in C++.

Dernier commit 24 mai 2018

This is the code for the "How to Deploy a Keras Model to Production" by Siraj Raval on Youtube

Dernier commit 6 juin 2017