Feature Based Audio Synthesis in the Web Audio API

graph audio features of Spotify tracks using the Spotify Web API

The home assistant

Predict song genre using XGBoost gradient boosting

Data analysis on my monthly playlists

Code used in the article "SATIN: A Persistent Musical Database for Music Information Retrieval" by Yann Bayle, Pierre Hanna and Matthias Robine in CBMI 2017. SATIN is a MIR dataset for reproducible research.

Spotify recommendations bot

Draw insights on Spotify users’ musical tastes and generate playlists tailored to either a single user or a group of users by analyzing their Top 100 tracks.

A Web App For Exploring Spotify Data using GraphQL

Analysis of Spotify's Top Tracks of 2017 in R

Package for automatic beat-mixing of music files in Python 🐻🎚

Show trends about your music listening habits over time. Create playlists from a given seed and specified audio features.

An implementation of a DNN speech recognizer as part of the Udacity NLP NanoDegree program

Features from audio: Spectrogram, (Wavelet Transform) Scalogram, (Q Transform) Spectrogram

Pernahkah terpikirkan bahwa suara khususnya musik dapat diklasifikasikan berdasarkan genrenya. Hal ini dikarenakan setiap musik memiliki audio features yang berbeda sesuai genrenya. Energy, accousticness, danceability, loudness, speechiness, tempo dan valence merupakan audio features yang saya gunakan dalam mengklasifikan genre musik menggunakan…

Audio feature extraction engine based on VAMP plugins

A server for JAMS data

Temporal audio features extraction by Librosa.

Audio Commons Audio Extractor

R data package centered on Spotify’s Top 200 Most Streamed songs in the U.S. Includes audio features, rankings and artist-specific information for every song which reached the top 200 between January 1, 2017 and December 2019.