AI powered speech denoising and enhancement
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Updated
May 29, 2024 - Python
AI powered speech denoising and enhancement
logWMSE, an audio quality metric & loss function with support for digital silence target. Useful for training and evaluating audio source separation systems.
Official repository of Spiking-FullSubNet, the Intel N-DNS Challenge Algorithmic Track Winner.
This repository contains a PyTorch implementation of U-Net applied on mel-spectograms of audio files for speech denoising.
Unofficial implementation of ResGrad: Residual Denoising Diffusion Probabilistic Models for Text to Speech
NNSE (Neural Network Speech Enhancement) is a speech-denoiser optimized to run on Ambiq's low power platform
Official PyTorch Implementation of CleanUNet (ICASSP 2022)
Denoising speech audio using different types of CNN's combined with MFCC's.
Source code for the paper titled "Speech Denoising without Clean Training Data: a Noise2Noise Approach". Paper accepted at the INTERSPEECH 2021 conference. This paper tackles the problem of the heavy dependence of clean speech data required by deep learning based audio denoising methods by showing that it is possible to train deep speech denoisi…
Tensorflow 2.x implementation of the DTLN real time speech denoising model. With TF-lite, ONNX and real-time audio processing support.
A neural network for end-to-end speech denoising
A self-supervised speech denoising strategy named Only-Noisy Training (ONT), which solves the speech denoising problem with only noisy audio signals in audio space for the first time.
About Implementation and training of a deep neural network for speech denoising tasks.
Time-Frequency Regularized Overlapping Group Shrinkage
An implementation of the paper MetricGAN (ICML 2019) in pytorch with some changes.
Deep Recurrent Neural Networks for Source Separation
Removing noise from speech using 1-D & 2-D Convolutional Neural Network (CNN)
A solution of "Bandai Namco Data Science Challenge." The task is to estimate clean mel-spectrogram by removing noise from artificially contaminated noisy one.
A curated list of awesome Speech Enhancement papers, libraries, datasets, and other resources.
A statistical model-based Speech Enhancement Using MMSE-STSA
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