yunzqq
I am currently a Postdoctoral Research Fellow at the HLT lab of the National University of Singapore. Research for fun.
National University of SingaporeSingapore
Pinned Repositories
addons
Useful extra functionality for TensorFlow 2.x maintained by SIG-addons
asteroid
The PyTorch-based audio source separation toolkit for researchers || Current highlight : we got our WHAMR results check it out here !
auditory-model-denoising
CMWTAT_Digital_Edition
win10激活工具,火绒不报错,开源工具。永久数字证书。😂原理好像是,先kms激活win10,👍再用用Win7兼容性模式运行官方的gatherosstate.exe数字权利激活工具。
CNN-FC
DeepComplexUNetPyTorch
Implementation of Deep Complex UNet Using PyTorch
DeepMMSE
DeepMMSE: A Deep Learning Approach to MMSE-based Noise Power Spectral Density Estimation
DeepXi
DeepXi: Residual Network-based A Priori SNR Estimator for Speech Enhancement
demucs
Code for the paper Music Source Separation in the Waveform Domain
dragen1860-Deep-Learning-with-TensorFlow-book
yunzqq's Repositories
yunzqq/DeepMMSE
DeepMMSE: A Deep Learning Approach to MMSE-based Noise Power Spectral Density Estimation
yunzqq/DeepXi
DeepXi: Residual Network-based A Priori SNR Estimator for Speech Enhancement
yunzqq/addons
Useful extra functionality for TensorFlow 2.x maintained by SIG-addons
yunzqq/asteroid
The PyTorch-based audio source separation toolkit for researchers || Current highlight : we got our WHAMR results check it out here !
yunzqq/auditory-model-denoising
yunzqq/CMWTAT_Digital_Edition
win10激活工具,火绒不报错,开源工具。永久数字证书。😂原理好像是,先kms激活win10,👍再用用Win7兼容性模式运行官方的gatherosstate.exe数字权利激活工具。
yunzqq/CNN-FC
yunzqq/DeepComplexUNetPyTorch
Implementation of Deep Complex UNet Using PyTorch
yunzqq/demucs
Code for the paper Music Source Separation in the Waveform Domain
yunzqq/dragen1860-Deep-Learning-with-TensorFlow-book
yunzqq/gpuRIR
Python library for Room Impulse Response (RIR) simulation with GPU acceleration
yunzqq/image2reverb
[ICCV 2021] Image2Reverb: Cross-Modal Reverb Impulse Response Synthesis.
yunzqq/jiwer
Evaluate your speech-to-text system with similarity measures such as word error rate (WER)
yunzqq/Keras-GAN
Keras implementations of Generative Adversarial Networks.
yunzqq/LPCTron
Tacotron2 + LPCNET for complete End-to-End TTS System
yunzqq/ml-art-colabs
A list of Machine Learning Art Colabs
yunzqq/onssen
An open-source speech separation and enhancement library
yunzqq/pysepm
Python implementation of performance metrics in Loizou's Speech Enhancement book
yunzqq/pystoi
Python implementation of the Short Term Objective Intelligibility measure
yunzqq/RDL-SE
Deep Residual-Dense Lattice Network for Speech Enhancement
yunzqq/speechbrain
A PyTorch-based Speech Toolkit
yunzqq/SSL_Anti-spoofing
This repository includes the code to reproduce our paper "Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentation".
yunzqq/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.
yunzqq/Tensorflow-Cookbook
Simple Tensorflow Cookbook for easy-to-use
yunzqq/tensorflow2_tutorials_chinese
tensorflow2中文教程,持续更新(当前版本:tensorflow2.0),tag: tensorflow 2.0 tutorials
yunzqq/Text-Classification
Implementation of papers for text classification task on DBpedia
yunzqq/yunzqq
Config files for my GitHub profile.
yunzqq/ast
Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".
yunzqq/diffwave
DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.
yunzqq/FSQ
Keras implement of Finite Scalar Quantization