Baby Cry Classification Using Machine Learning

Authors : P.Ithaya Rani; P.Pavan Kumar; V.Moses Immanuel; P.Tharun; P.Rajesh

Volume/Issue : Volume 7 - 2022, Issue 3 - March

Google Scholar :

Scribd :


A Cry is a type of correspondence for kids to communicate their sentiments. Child cry can be portrayed by its regular occasional tone and the difference in voice. Through their child's cry discovery, guardians can screen their child somewhat just in significant conditions. Recognition of a child cry in discourse signals is a urgent advance in applications like remote child observing and it is likewise significant for researchers, who concentrate on the connection between child cry signal examples and other formative boundaries. This investigation of sound acknowledgment includes highlight extraction and arrangement by deciding the sound example. We use MFCC as an element extraction strategy and K-Nearest Neighbor (K-NN) for arrangement. K-Nearest Neighbor (KNN) is a characterization technique that is regularly utilized for sound information. The KNN classifier is displayed to yield extensively better outcomes contrasted with different classifiers.


Paper Submission Last Date
30 - April - 2024

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.