Skip to content

Surgical mask detection. Discriminate between utterances (audio files) with and without surgical mask

Notifications You must be signed in to change notification settings

AndraRaco/MachineLearning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 

Repository files navigation

Machine Learning

I. Laboratories: https://fmi-unibuc-ia.github.io/ia/

II. Surgical mask detection Project

In the surgical mask detection task, participants have to discriminate between utterances with and without surgical masks. The system could be useful in the context of the COVID-19 pandemic, by allowing the automatic verification of surgical mask wearing from speech. This is a binary classification task in which an utterance (audio file) must be labeled as without mask (label 0) or with mask (label 1).

The training data is composed of 8000 audio files. The validation set is composed of 1000 audio files. The test is composed of 3000 audio files.

File Descriptions

train.txt - the training metadata file containing the audio file names and the corresponding labels (one example per row) validation.txt - the validation metadata file containing the audio file names and the corresponding labels (one example per row) test.txt - the test metadata file containing the audio file names (one sample per row) sample_submission.txt - a sample submission file in the correct format

Kaggle competition: https://www.kaggle.com/c/ml-fmi-23-2020/overview

Documentation: https://github.com/AndraRaco/MachineLearning/blob/master/Surgical%20mask%20detection%20Project/Surgical%20mask%20detection%20Documentation.pdf

Project: https://github.com/AndraRaco/MachineLearning/blob/master/Surgical%20mask%20detection%20Project/Surgical%20mask%20detection.ipynb

About

Surgical mask detection. Discriminate between utterances (audio files) with and without surgical mask

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published