Mohamed Nabih's repositories
ComplexCNN
pytorch implementation of complex convolutional neural network
Conv-TasNet-PyTorch
A PyTorch implementation of Conv-TasNet
CTC_pytorch
CTC end -to-end ASR for timit and 863 corpus.
Data-Science-cheet-sheets
Cheat sheets for Numpy, Pandas, SQL, Scikit Learn
Listen-Attend-and-Spell-Pytorch
Listen Attend and Spell (LAS) implement in pytorch
maracas
maracas is a library for corrupting audio files with additive and convolutive noise.
pykaldi2
Yet another speech toolkit based on Kaldi and PyTorch
pytorch-asr
ASR with PyTorch
pytorch-beginner
pytorch tutorial for beginners
pytorch-kaldi
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
pytorch-speech-commands
Speech commands recognition with PyTorch
PyTorch-Tutorial-1
Build your neural network easy and fast
pytorch-tutorials-examples-and-books
PyTorch1.x tutorials, examples and some books I found 【不定期更新中】整理的PyTorch 1.x 最新版教程、例子和书籍
Pytorch_bootcamp_Udemy
Course code for PyTorch for Deep Learning with Python Bootcamp
pytorch_MLP_for_ASR
This code implements a basic MLP for speech recognition. The MLP is trained with pytorch, while feature extraction, alignments, and decoding are performed with Kaldi. The current implementation supports dropout and batch normalization. An example for phoneme recognition using the standard TIMIT dataset is provided.
SEGAN
A PyTorch implementation of SEGAN based on INTERSPEECH 2017 paper "SEGAN: Speech Enhancement Generative Adversarial Network"
segan-pytorch
SEGAN pytorch implementation https://arxiv.org/abs/1703.09452
segan_pytorch
Speech Enhancement Generative Adversarial Network in PyTorch
spec_augment
🔦 A Pytorch implementation of GoogleBrain's SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
Speech_Enhancement_MMSE-STSA
A statistical model-based Speech Enhancement Using MMSE-STSA
stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
stanford-cs-230-deep-learning
VIP cheatsheets for Stanford's CS 230 Deep Learning
traditional-speech-enhancement
Spectral Subtraction, Wiener Filtering, MMSE
VQ-VAE-Speech
PyTorch implementation of VQ-VAE + WaveNet by [Chorowski et al., 2019] and VQ-VAE on speech signals by [van den Oord et al., 2017]