DESIGNING A NEW DATA COLLECTION APPROACH

Abstract

Building a quick, efficient and cheap cough classification tool is a very challenging task. It requires a well-thought and rigorous approach. One of the main take-outs behind this tool would be a carefully collected dataset which can serve as a golden high-quality baseline for building an accurate machine learning model. This study intends to build a new data collection tool and analyze the collected dataset in order to be able to differentiate between various types of cough audio signals. There are very limited efforts that aimed to create a high reliability cough audio signals dataset that is quality controlled by the healthcare professionals. The current dataset contains eight types of coughs plus an additional ’other’ type. The primary goal is to design and build a new data collection approach for the Cough Analyzer application and secondly to conduct a data analysis of the collected dataset which contains 1100+ entries to date submitted by the people from around the world.