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A latent text-to-image diffusion model
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable…
A simple screen parsing tool towards pure vision based GUI agent
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
QLoRA: Efficient Finetuning of Quantized LLMs
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
Think DSP: Digital Signal Processing in Python, by Allen B. Downey.
Unofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN & HiFi-GAN & StyleMelGAN) with Pytorch
Noise reduction in python using spectral gating (speech, bioacoustics, audio, time-domain signals)
Demonstrations of Magenta Models
Implementations of a number of generative models in Tensorflow 2. GAN, VAE, Seq2Seq, VAEGAN, GAIA, Spectrogram Inversion. Everything is self contained in a jupyter notebook for easy export to colab.
Official implementation of Diffusion Autoencoders
This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.
Tutorial on creating your own GAN in Tensorflow
Collection of notebooks and scripts related to audio processing and machine learning.
Classical algorithms of sound source localization with beamforming, TDOA and high-resolution spectral estimation.
A sample code of data augmentation methods for wearable sensor data (time-series data)
sEMG-based gesture recognition using deep learnig
Code for SuDoRm-Rf networks for efficient audio source separation. SuDoRm-Rf stands for SUccessive DOwnsampling and Resampling of Multi-Resolution Features which enables a more efficient way of sep…
Two-talker Speech Separation with LSTM/BLSTM by Permutation Invariant Training method.
Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51
Tensorflow 2.0 implementation of the paper: A Fully Convolutional Neural Network for Speech Enhancement
PyTorch Implementation of FastSpeech 2 : Fast and High-Quality End-to-End Text to Speech
Some Jupyter notebooks about audio signal processing with Python
Spectrograms, MFCCs, and Inversion Demo in a jupyter notebook
Audio Denoising with Deep Network Priors