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 like AirPods, which millions of people use daily [1]. Melodic EQ was inspired by these users to create the best audio listening experience for listeners with various preferences [2]. Melodic EQ is a project that creates custom EQs to the user's custom music tastes and filters the audio to fit their favorite settings. To achieve this goal, the process starts with a song file taken from an existing file, for example, Spotify downloads or mp3s. This file is then uploaded to the app. The software sorts the song in a genre detecting Algorithm and assigns a genre label to that song. Inside the app, the user will create or select EQs for that genre and apply it to their music. The interface is easy to use and the app aims to make everyone's preferences achievable and on the fly. That’s why there are presets for each category 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 equalizer network