Skip to content

Classification Machine learning model to predict Gender based on various Acoustic parameters

Notifications You must be signed in to change notification settings

akulkarni5208/Internship_project-Gender-predection-using-machine-learning-algorithms-

Repository files navigation

Internship_project(Gender predection using machine learning algorithms)

Problem statement:

Create a classification model to predict the gender (male or female) based on different acoustic parameters

Context:

This database was created to identify a voice as male or female, based upon acoustic properties of the voice and speech. The dataset consists of 3,168 recorded voice samples, collected from male and female speakers. The voice samples are preprocessed by acoustic analysis in R using the seewave and tuneR packages, with an analyzed frequency range of 0hz-280hz (human vocal range).

Column Description:

imageimage

Classifier Algorithms used:

image

Dataset:

https://drive.google.com/file/d/1OqjMamx5LuejWLbQXJOrvwCXu5nAZr96/view?usp=sharing

Conclusion :

image

From the above bar graph which shows the accuracy of different classifiers , it is pretty evident that Random Forest Classifier reported with best accuracy compared to other algorithms with 98% Accuracy.

About

Classification Machine learning model to predict Gender based on various Acoustic parameters

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published