YijinMao
Graduate Student, School of Informatics, Xiamen University
School of Informatics, Xiamen UniversityXiamen, CHN
YijinMao's Stars
facebookresearch/fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
dair-ai/ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
asteroid-team/asteroid
The PyTorch-based audio source separation toolkit for researchers
jim-schwoebel/voice_datasets
🔊 A comprehensive list of open-source datasets for voice and sound computing (95+ datasets).
thuml/TimesNet
About Code release for "TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis" (ICLR 2023), https://openreview.net/pdf?id=ju_Uqw384Oq
ddlBoJack/emotion2vec
[ACL 2024] Official PyTorch code for extracting features and training downstream models with emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation
google-research/sound-separation
sp-uhh/sgmse
Score-based Generative Models (Diffusion Models) for Speech Enhancement and Dereverberation
f90/Wave-U-Net-Pytorch
Improved Wave-U-Net implemented in Pytorch
haoxiangsnr/A-Convolutional-Recurrent-Neural-Network-for-Real-Time-Speech-Enhancement
A minimum unofficial implementation of the "A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement" (CRN) using PyTorch
AiRanthem/xmu-daily-report
长期维护,无需本地部署,在线fork仓库即可使用的厦大Daily Health Report 健康打卡自动填写脚本
madhavmk/Noise2Noise-audio_denoising_without_clean_training_data
Source code for the paper titled "Speech Denoising without Clean Training Data: a Noise2Noise Approach". Paper accepted at the INTERSPEECH 2021 conference. This paper tackles the problem of the heavy dependence of clean speech data required by deep learning based audio denoising methods by showing that it is possible to train deep speech denoising networks using only noisy speech samples.
eastmountyxz/HWCloudImageRecognition
该资源是作者在华为云撰写《从零到壹Python图像处理及识别》电子书和源代码,全书648页48章,涵盖图像处理、图像识别和图像增强,基础入门书籍希望对大家有所帮助,且看且珍惜~
polarch/Spherical-Array-Processing
A collection of MATLAB routines for acoustical array processing on spherical harmonic signals, commonly captured with a spherical microphone array.
zoam/xmu-thesis-grd
厦门大学研究生学位论文 LaTeX 模板
zhoudaxia233/EfficientUnet-PyTorch
A PyTorch 1.0 Implementation of Unet with EfficientNet as encoder
CUHK-AIM-Group/Endora
Endora: Video Generation Models as Endoscopy Simulators (MICCAI 2024)
pheepa/DCUnet
Phase-aware speech enchancement with Deep Complex U-Net
matsuolab/T3A
This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2021, Spotlight)
huyouare/WaveNet-Theano
Implementation of WaveNet: A Generative Model for Raw Audio
posenhuang/singingvoiceseparationrpca
Singing-Voice Separation From Monaural Recordings Using Robust Principal Component Analysis
liqingchunnnn/Only-Noisy-Training
A self-supervised speech denoising strategy named Only-Noisy Training (ONT), which solves the speech denoising problem with only noisy audio signals in audio space for the first time.
AIM3-RUC/MERC_Challenge_CCAC2023
Multimodal Emotion Recognition in Conversation Challenge( CCAC 2023)
sony/CLIPSep
TowerYsable/speech_enhancement_awesome
mah533/Synthetic-ECG-Signal-Generation-using-Probabilistic-Diffusion-Models
We used Improved DDPM (developed by OpenAI) to generate synthetic ECG signals and compared it with WGAN-GP.
TanUkkii007/wavenet
An implementation of WaveNet: A Generative Model for Raw Audio https://arxiv.org/abs/1609.03499
ZhuGeComing/Matlab-project
Matlab日常学习记录
chrisacc/EigenDecomposition
CUDA implementation of eigen decomposition of many moderate sized, real symmetric matrices
huanranchen/T3A
unofficial pytorch implement of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization