happypanda5's repositories
AMI-Cough-Annotations
Annotations of cough events in the AMI corpus audio recordings
AMI_cough_re-annotation
Re-annotation of cough events present in the AMI corpus.
audio-seg-data-synth
Artificially synthesising data for audio segmentation to improve music-speech detection
cough-analysis
In pursuit of COVID-19 through cough analysis
Cough-Detection
Implements data-driven approaches for the detection of coughs in patients with respiratory illnesses.
cough-research-papers
Collection of research papers on cough classification
Cough-signal-processing
Different methods and techniques for features extraction from audio
cough_detection
cough detection task
CoughDetection
ECE 284 Mobile Health Sensing - Group 5
Covid_Cough_Test
Predicting if the user is COVID positive or negative based on audio sample of his cough. Accuracy is 89%
data-gen-keras
This repository is associated with the blog post on "Data Generators with Keras and Tensorflow on Google Colab"
Deep-Virtual-Rapport-Agent
Deep virtual rapport agent & Head gesture detector
DepAudioNet
Reproduction of DepAudioNet by Ma et al (AVEC2016)
DepAudioNet_reproduction
Reproduction of DepAudioNet by Ma et al. {DepAudioNet: An Efficient Deep Model for Audio based Depression Classification,(https://dl.acm.org/doi/10.1145/2988257.2988267), AVEC 2016}
DiscoveryRNNs
Discovery RNNs, explainable RNN saliency visualization, and its application to unsupervised segmentation of COVID-19 forced coughs
kdd2020-calibration
How to calibrate your neural network classifier: Getting accurate probabilities from a classification model
medinfo2019-sa-risk
Files related to the MedInfo2019 submission "Text Classification to Inform Suicide Risk Assessment in Electronic Health Records"
Memes_DH2020
Repository to host a corpus of meme texts for a project presented at the DH 2020 conference
OSF-Audio-Classification
Machine learning models for OSF cough audio data classification
Project-COVgh-V1
1. Project is created with intenction to detect/classify an audio signal if it is such as a cough or sneeze audio signal. 2. Further goal is to pipeline this to mobile applications to narrow the detection of sickness audio specificlly of a COVID19. 3. To contribute to help gov authorities to identify the persons with probable coronavirus infection living among us. ("We should fight the Virus, not the Patient effected with virus")