iPwnXX's Stars
10x-Engineers/Infinite-ISP
A camera ISP (image signal processor) pipeline that contains modules with simple to complex algorithms implemented at the application level.
WenzheLiu-Speech/sound-source-localization-algorithm_DOA_estimation
关于语音信号声源定位DOA估计所用的一些传统算法
suno-ai/bark
🔊 Text-Prompted Generative Audio Model
Rikorose/DeepFilterNet
Noise supression using deep filtering
wenet-e2e/wenet
Production First and Production Ready End-to-End Speech Recognition Toolkit
k2-fsa/k2
FSA/FST algorithms, differentiable, with PyTorch compatibility.
google-research/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
seanwood/gcc-nmf
Real-time GCC-NMF Blind Speech Separation and Enhancement
breizhn/DTLN
Tensorflow 2.x implementation of the DTLN real time speech denoising model. With TF-lite, ONNX and real-time audio processing support.
aoifemcdonagh/audioset-processing
Toolkit for downloading and processing Google's AudioSet dataset.
PKUFlyingPig/cs-self-learning
计算机自学指南
SUSTech-CRA/sustech-master-thesis
南方科技大学研究生学位论文LaTeX模板
nanahou/Awesome-Speech-Enhancement
A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.
github/gitignore
A collection of useful .gitignore templates
jupyterlite/jupyterlite
Wasm powered Jupyter running in the browser 💡
jorgengrythe/beamforming
Matlab files for various types of beamforming
creiser/drone-detection
Bounding box detection of drones (small scale quadcopters) with CNTK Fast R-CNN
Edresson/VoiceSplit
VoiceSplit: Targeted Voice Separation by Speaker-Conditioned Spectrogram
ageron/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Xxxxhx/SUSTech-Daily-Health-Auto-Submitter
This is a daily health auto submitter for SUSTech students
machinelearningnanodegree/stanford-cs231
Resources for students in the Udacity's Machine Learning Engineer Nanodegree to work through Stanford's Convolutional Neural Networks for Visual Recognition course (CS231n).