Music Genres Classification using KNN System

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Nevon Driver Drowsiness Detection System Using Python
nevon software

One way of categorizing and organizing music is based on the genre, which is identified by some characteristics of the music such as rhythmic structure, harmonic content and instrumentation. Being able to automatically classify and provide tags to the music present in a user’s library, based on genre. A music genre is a conventional category that predicts the genre of music belonging to tradition or a set of conventions. Categorizing music files according to their genre is a challenging task in the area of music information retrieval.

Our Music Genres Classification System will detect the music from the audio file. Once the music is detected, the system will further continue to classification. As a result, the system will display the music genre. So, for this system, there are a predefined set of music genres that the system will classify.

In this system, the user will need to register their account first to log in to the system. They can log in using their username and password. The system will detect the music genre and classify them. Once the system detects and identifies the music, the results will be then displayed to the user. The user will only need to upload an audio file from their device. The front-end involves Html, CSS, and JavaScript and the back-end involves Python. The framework used is Django and the database is MySQL. Here, we have implemented the k-nearest neighbor (KNN) algorithm for classification.

Also, we will be using the GTZAN genre classification dataset for training our model. The type of music genres that our system will be able the classify are: blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, and rock.


  • It is easy to maintain.
  • It is user-friendly.
  • The system can easily detect music and classify the music genres from the audio file.