jefflai108 Goto Github PK

6.864-final

assert

JHU's system submission to the ASVspoof 2019 Challenge: Anti-Spoofing with Squeeze-Excitation and Residual neTworks (ASSERT).

attentive-filtering-network

University of Edinbrugh-Johns Hopkins University's system for ASVspoof 2017 Version 2.0 dataset.

av-nsl

axlearn

cohere_proj

A web-app that tracks how well a patient with schizophrenia is responding to treatment and identifies at-risk (prodromal) individuals based on semantic and syntactic analysis of patient text samples.

contrastive-predictive-coding-pytorch

Contrastive Predictive Coding for Automatic Speaker Verification

cyclegan

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

data_structures

dim

Deep InfoMax (DIM), or "Learning Deep Representations by Mutual Information Estimation and Maximization"

espnet

End-to-End Speech Processing Toolkit

factorizedhierarchicalvae

This repository contains the code to reproduce the core results from the paper "Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data"

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

fairseq-ust

holed_up

Mechatronics Spring 2017 Final Project: A emergency rescue system.

intermediate_programming

intro-machine-learning-paper

Paper I have read for understanding statistical machine learning and speaker recognition

intro_computing

intro_mechatronics

Introduction to Mechatronics (EN.520.240) is an introductory robotic course I took in Fall 2016 at Johns Hopkins University. The course consists of 7 labs and a final project, and each one builds up to the next one. The codes are written for Arduino, and each subfile corresponds to a lab.

java

jefflai108.github.io

joint-segmentation

kaldi-io-for-python

Python functions for reading kaldi data formats. Useful for rapid prototyping with python.

kruschke-doing_bayesian_data_analysis

John K. Kruschke's Doing Bayesian Data Analysis: A Tutorial with R and BUGS

lda

An implementation of Linear Discriminant Analysis on multi-class speaker recognition.

lexicon-learner

lstm

Voice activity detection of noisy speech files with LSTM. LSTM is implemented with Keras. Data processing is done with Python, MATLAB, and Bash. Experiments are done on Johns Hopkins CLSP GPUs.

mfcc

Steps to extract mfcc features from audios

neurodo

[Finalist | MedHacks] A web tool for the analysis of cognitive dysfunction in patient journaling during Schizophrenia clinical drug trials

noise_cancellation

Noise cancellation system for speech files with different kinds of noise.