Musicmap attempts to provide the ultimate genealogy of popular music genres, including their relations and history. It is the result of more than seven years of research with over 200 listed sources and cross examination of many other visual genealogies. Its aim is to focus on the delicate balance between comprehensibility, accuracy and accessibility. In other words: the ideal genealogy is not only complete and correct, but also easy to understand despite its complexity. This is a utopian balance that can never be achieved but only approached. By choosing the right amount of genres, determining forms of hierarchy and analogy and ordering everything in a logical but authentic manner, a satisfactory balance can be obtained. Said balance is always the main subject of discussion in music genre genealogies and the capital reason why an absolute visual reference has been absent thus far (and probably always will be). Musicmap is a platform in search for the perfect balance of popular music genres to provide a powerful tool for educational means or a complementary framework in the field of music metadata and automatic taxonomy.
TheAudioDB is a community database of audio artwork and data with a JSON API.
Last.fm is a music service that learns what you love.
Create your own profile, track what you listen to (we call this scrobbling) and get cool stuff like your own music charts, new music recommendations, and a big ol’ community of other music lovers.
Free Music Downloads
Common Music (CM) is a real-time music composition system implemented in JUCE/C++ and Scheme. It generates musical output via MIDI, OSC, CLM, FOMUS and CSOUND. Its user application is called GRACE (Graphical Real-time Algorithmic Composition Environment)
- Algorithmic music composition environment
- Runs on Mac, Windows and Linux
- Real time scheduling of musical algorithms
- Two coding languages for designing algorithms: S7 Scheme and SAL (an easy-to-learn alternate)
- MIDI input/output
- CLM/Sndlib audio system built in (Scottstaedt)
- CCRMA digital audio instrument definitions built in (Scottstaedt)
- Open Sound Control input/output
- Metronomes and running algorithm redefinition for live coding
- Data visualization
- Music pattern definitions
- Fomus system built in for computing music notations (Psenicka)
This is a “musical spectrum”, displayed accordingly to how the spectrum is divided in music (notes, semitones, etc).
ABC, developed by Chris Walshaw, is a format designed to notate music using plain text. It was originally designed for folk tunes of Western European origin which can be written on one staff, but has since been extended to support the notation of complete, classical music scores.
Since its introduction at the end of 1991, ABC has become very popular. Programs on many operating systems use ABC as an input and/or output format. There are programs which produce printed sheet music or allow for computer performances, search in tune databases, or that analyze tunes in some way.
The aim of this project is to promote the ABC language by maintaining the ABC standard and a set of software and source code that manipulate and present music written in ABC.
Classical music extensions for the ABC music notation language.
ABC to HTML ~ sourceforge.net/projects/netabc/
User Interfaces ~ https://sourceforge.net/projects/runabc/
An internet repository for permanent storage of quality music modules from the tracking and demo scene. The Mod Archive began collecting music modules back in 1996. Since then, it has grown and become one of the largest and oldest collections online, thanks to the artists that contributed to The Mod Archive and the Public Domain in general.
Algorithms and Interactive Tools for Exploring Music Composition, Analysis, and Interdisciplinary Learning.
This web site has interactive tools that provide a unique learning experience for users, regardless of their musical training. Students of music composition can explore algorithmic composition, while others can create musical representations of models for the purpose of aural interpretation and analysis. Here, the algorithmic process is used in a creative context so that users can convert sequences of numbers into sounds.
We’ve created MuseNet, a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles. MuseNet was not explicitly programmed with our understanding of music, but instead discovered patterns of harmony, rhythm, and style by learning to predict the next token in hundreds of thousands of MIDI files. MuseNet uses the same general-purpose unsupervised technology as GPT-2, a large-scale transformer model trained to predict the next token in a sequence, whether audio or text.