Audio feature extraction for JavaScript.
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Updated
Jun 12, 2024 - TypeScript
Audio feature extraction for JavaScript.
A library for audio and music analysis, feature extraction.
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)
🎶 Predicting Billboard's Year-End Hot 100 Songs using audio features from Spotify and lyrics from Musixmatch
This project is designed to analyze Spotify stream history metadata, extract audio features using the Spotify Web API, and generate a personalized playlist based on a trained neural network model.
Python to generate a customized Spotify playlist based on historic user listening data
Estratto is a powerful and user-friendly Rust library designed for extracting rich audio features from digital audio signals.
The aim of this project is to map and analyse the sentiments of different countries based on their music tastes over time. The data is presented in a web app coded in Python using the Plotly Dash package.
C++ code 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)
Evolving Artificial Neural Networks for Cross-Adaptive Audio Effects
Fast and simple music and audio analysis using RNN in Python 🕵️♀️ 🥁
Extract frequency, power, width and dissonance of formants from wav files
Audio input -> real-time analysis -> OSC output. Takes in real-time audio, does feature extraction using smart algorithms then sends out OSC to be used in other programs.
This may become an audio feature extraction library for Rust.
Analysis of the audio features from my weekly top tracks from Spotify using the library Spotipy to support the API extraction
A Shiny App to Retrieve Daily Top 200 Spotify Charts with Audio Features in Real-Time
Audio processing, Video processing and Computer Vision (UC3M - C2.350.16508)
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