CaoYuhang

Yuhang's repositories

Speech_Enhancement_MMSE-STSA

A statistical model-based Speech Enhancement Using MMSE-STSA

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GroupSparseLP_dereverberation

This code solves multichannel sparse linear prediction using the Least Absolute Deviation (LAD) and Group LASSO (GL) algorithms with applications in dereverberation

Language:MATLABGPL-3.0000

gperftools

Main gperftools repository

Language:C++BSD-3-Clause000

sednn

deep learning based speech enhancement using keras python, make it easy to use

Language:Python000

practical-machine-learning-with-python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

Language:Jupyter NotebookApache-2.0100

dlbook_notation

LaTeX files for the Deep Learning book notation

Language:TeX000

essentia

C++ library for audio and music analysis, description and synthesis, including Python bindings

Language:Jupyter NotebookAGPL-3.0000

opensmile

A github repo of the openSMILE feature extraction tool.

Language:C++NOASSERTION000

Chainer_Mask_R-CNN

Implementation of Mask R-CNN in Chainer

Language:PythonNOASSERTION000

beamforming

Matlab files for various types of beamforming

Language:Matlab000

codingprofiling

A collection of c/c++ program profiling tools usage. Include perf/gprof/valgrind/oprofile

Language:C000

SoundZone_Tools

Signal Processing Tools for MATLAB

GPL-2.0000

Algorithms

Assignments for coursera's stanford algorithm's specialization

Language:C++000

mopo

Modular and Polyphonic audio synthesis library

GPL-3.0000

segan

Speech Enhancement Generative Adversarial Network

Language:PythonMIT000

PRML-Code

demo code of machine learning book prml

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Sum-of-Functions-Optimizer

Implements SFO minibatch optimizer in Python and MATLAB, and reproduces figures from paper.

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fast-wavenet

Efficient implementation of Wavenet generation.

GPL-3.0000

Simulation code for “Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure” by Emil Björnson, Mats Bengtsson, and Björn Ottersten, IEEE Signal Processing Magazine, vol. 31, no. 4, pp. 142-148, July 2014.

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Active-Noise-Cancellation-System

LMS, RLS, QR-RLS based FIR adaptive filter for active noise cancellation with and without quantization effects.

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Noise-reduction

Noise reduction using Log_MMSE method implement by C language

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choltest

Test of cholesky factor updating