Amirpasha Mobini Tehrani's repositories
audio-diffusion-pytorch-fork
Audio generation using diffusion models, in PyTorch.
CleanUNet
Official PyTorch Implementation of CleanUNet (ICASSP 2022)
DeepFilterNet
Noise supression using deep filtering
denoiser
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 archi
DNS-Challenge
This repo contains the scripts, models, and required files for the Deep Noise Suppression (DNS) Challenge.
Generative-Adversarial-Networks-GANs-Specialization
Deeplearning.AI Generative Adversarial Networks (GANs) Specialization Solution
MelGAN-VC
MelGAN-VC: Voice Conversion and Audio Style Transfer on arbitrarily long samples using Spectrograms
GenerativeDeepLearning
The official code repository for examples in the O'Reilly book 'Generative Deep Learning'
LoopGAN
StyleGAN2 + MelGAN Audio Loop Generation
LoopTest
Official repo of ISMIR-21 publication, “A Benchmarking Initiative for Audio-domain Music Generation using the FreeSound Loop Dataset”.
MelGAN
GAN-based Mel-Spectrogram Inversion Network for Text-to-Speech Synthesis
musicinformationretrieval
Instructional notebooks on music information retrieval.
Neural-Style-Transfer-Audio
This is PyTorch Implementation of Neural Style Transfer Algorithm which is modified for Audios.
RAVE
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
Scyclone
Real-time Neural Timbre Transfer
stylegan2
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
TRUNet
unofficial PyTorch implementation of 《REAL-TIME DENOISING AND DEREVERBERATION WTIH TINY RECURRENT U-NET》
vector-quantize
Vector Quantization in Pytorch
vschaos
Lavish audio synthesis from unfathomable variational abysses