Academy & Industry Research Collaboration Center (AIRCC)

Volume 13, Number 05, March 2023

A Fully Automated Music Equalizer based on Music Genre Detection using Deep Learning and Neural Network


Kevin Hu1, Yu Sun2, Yujia Zhang3, 1USA, 2California State Polytechnic University, USA, 3University of California Irvine, USA


Recent years have witnessed the dramatic popularity of online music streaming and the use of headphones likeAirPods, which millions of people use daily [1]. Melodic EQ was inspired by these users to create the best audiolistening experience for listeners with various preferences [2]. Melodic EQ is a project that creates customEQs tothe user's custom music tastes and filters the audio to fit their favorite settings. To achieve this goal, the processstarts with a song file taken from an existing file, for example, Spotify downloads or mp3s. This file is then uploadedto the app. The software sorts the song in a genre detecting Algorithm and assigns a genre label to that song. Insidethe app, the user will create or select EQs for that genre and apply it to their music. The interface is easy to use andthe app aims to make everyone's preferences achievable and on the fly. That’s why there are presets for eachcategory for users who are unfamiliar with equalizers, and custom settings for advanced users to create their perfect sound for each genre.


AI auto genre detection, Automatic genre switching, EQ, Convolution music