mpariente repositories

:link: Some useful websites for programmers.

Last commit Jun 8, 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.

Last commit Feb 13, 2020

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

Last commit Apr 10, 2020

An open source dataset for source separation

Last commit May 25, 2020

First repository

Last commit Oct 29, 2018

Last commit Jun 5, 2020

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

Last commit Mar 30, 2020

A Pure-Python Real-Time Audio Library

Last commit Jun 27, 2018

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

Last commit Mar 16, 2020

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

Last commit Jul 31, 2020

simple audio I/O for pytorch

Last commit Jul 11, 2019

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

Last commit Nov 26, 2019

https://github.com/DataTalksClub

Last commit Jan 19, 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 👇🏼

Last commit Jan 15, 2026

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

Last commit Dec 4, 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.

Last commit Sep 4, 2020

End-to-End Speech Processing Toolkit

Last commit Aug 14, 2020

We'll see what this becomes

Last commit May 22, 2022

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

Last commit May 24, 2018

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

Last commit Jun 6, 2017