Categorize audio files by genre effortlessly. Use Dockerized environment and API to classify music genres.
Reproducible research code for the experiments presented in our article "Kara1k: a karaoke dataset for cover song identification and singing voice analysis" published at IEEE ISM 2017
An essentia-based tool for extracting features from a collection of audio files. Two simple user interfaces, to create playlists and explore track similarities based on extracted audio features and embeddings.
Dockerized benchmark model & API for classifying music by genre based on TensorFlow and Essentia
Neural network for classifying audio samples into categories. This was my BSc final year project.
Add a description, image, and links to the essentia topic page so that developers can more easily learn about it.
To associate your repository with the essentia topic, visit your repo's landing page and select "manage topics."