找人找不到北's starred repositories
TelegramGroup
2024最新悄咪咪收集的10000+个Telegram群合集，附带全网最有趣最好用的机器人BOT🤖【tg百科】
design-patterns-cpp
C++面向对象设计模式-文档与代码
http-parser
http request/response parser for c
InterviewGuide
🔥🔥「InterviewGuide」是阿秀从校园->职场多年计算机自学过程的记录以及学弟学妹们计算机校招&秋招经验总结文章的汇总，包括但不限于C/C++ 、Golang、JavaScript、Vue、操作系统、数据结构、计算机网络、MySQL、Redis等学习总结，坚持学习，持续成长！
leetcode-master
《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀
deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
AFRCNN-For-Speech-Separation
Speech Separation Using an Asynchronous Fully Recurrent Convolutional Neural Network
Attention-Is-All-You-Need-In-Speech-Separation
Speech Separation
Dual-Path-Transformer-Network-PyTorch
Unofficial implementation of Dual-Path Transformer Network (DPTNet) for speech separation (Interspeech 2020)
UtterancePIT-Speech-Separation
According to funcwj's uPIT, the training code supporting multi-gpu is written, and the Dataloader is reconstructed.
svoice
We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.
Dual-Path-RNN-Pytorch
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch
Conv-TasNet
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation Pytorch's Implement
Tutorial_Separation
This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.
speechbrain
A PyTorch-based Speech Toolkit
leaf-audio
LEAF is a learnable alternative to audio features such as mel-filterbanks, that can be initialized as an approximation of mel-filterbanks, and then be trained for the task at hand, while using a very small number of parameters.
Speech-Separation-Paper-Tutorial
A must-read paper for speech separation based on neural networks
leaf-pytorch
PyTorch implementation of the LEAF audio frontend
Loss-Gated-Learning
ICASSP 2022: 'Self-supervised Speaker Recognition with Loss-gated Learning'
Few-Shot_Sound_Event_Detection_with_Prototypical_Neural_Networks
A study in using metric-based Meta-Learning for Sound Event Detection