A library for audio and music analysis, feature extraction.
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Updated
May 24, 2024 - C
A library for audio and music analysis, feature extraction.
Audio feature extraction for JavaScript.
Extract video features from raw videos using multiple GPUs. We support RAFT flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, and TIMM models.
Python scripts accompanying the book "An Introduction to Audio Content Analysis" (www.AudioContentAnalysis.org)
Matlab scripts accompanying the book "An Introduction to Audio Content Analysis" (www.AudioContentAnalysis.org)
Fast and simple music and audio analysis using RNN in Python 🕵️♀️ 🥁
Audio Commons Audio Extractor
Package for automatic beat-mixing of music files in Python 🐻🎚
Emotional Video to Audio Transformation with ANFIS-DeepRNN (Vanilla RNN and LSTM-DeepRNN) [MPE 2020]
Spotify recommendations bot
Evolving Artificial Neural Networks for Cross-Adaptive Audio Effects
Extract frequency, power, width and dissonance of formants from wav files
Machine Learning and NLP was used to predict a song's genre based off its audio features and lyrics respectively. Users can test the models with lyrics they paste in onto our website.
🎶 Predicting Billboard's Year-End Hot 100 Songs using audio features from Spotify and lyrics from Musixmatch
Cross platform audio feature extraction and sound classification tool
Show trends about your music listening habits over time. Create playlists from a given seed and specified audio features.
C++ code accompanying the book "An Introduction to Audio Content Analysis" (www.AudioContentAnalysis.org)
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.
This may become an audio feature extraction library for Rust.
Data analysis on my monthly playlists
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