Baby cry detection and analysis
This project is developed on Python programming with Machine Learning algorithm, K-Nearest Neighbor (KNN) algorithm
The project used Audio pre-processing with MFCC technique to extract feature.
ML is used to train and detect the infant cry type. There are five types used in this project are
Belly Pain
Burping
Discomfort
Hungry
Tired
The project gets accuracy of 88% with KNN algorithm
Python Demo video