43 Open Source Mir Software Projects
Free and open source mir code projects including engines, APIs, generators, and tools.
💻📱 A cross platform system abstraction library written in C++ for managing windows and performing OS tasks.
Sustain Pedal Detection15 ⭐
Piano Sustain-Pedal Detection Using Convolutional Neural Networks and Transfer Learning
Mir Core18 ⭐
Base software building blocks: Algebraic types (aka sumtype/tagged union/variant), universal reflection API, basic math, and more.
Music Artist Classification Crnn55 ⭐
Supplementary material for IJCNN paper "Musical Artist Classification with Convolutoinal Recurrent Neural Networks"
Trained Cnn For Genre Classification12 ⭐
🎵 Trained CNN model for Genre classification on GTZAN dataset [CNN Model: https://github.com/Hguimaraes/gtzan.keras]
Jdcnet Pytorch15 ⭐
pytorch implementation of JDCNet, singing voice detection and classification network
AudioGuide is an OSX standalone program for concatenative sound synthesis written in python. Interacting with the program is done via textfiles written in a simple syntax. AudioGuide renders concatenations automatically using csound, but also includes support for Max, Logic, Reaper, Pro Tools, music notation via bach, and json files.
Field observation quick analysis toolkit (kw: field observation, air polltion, time series summary, time series resampling, average variation, ozone formation potential (OFP), MIR, tuv).
Evaluation metrics for machine-composed symbolic music. Paper: "The Jazz Transformer on the Front Line: Exploring the Shortcomings of AI-Composed Music through Quantitative Measures", ISMIR 2020
Course about artificial intelligence applied to the arts. Available in spanish and english.
Audio degradation toolbox in python, with a command-line tool. It is useful to apply controlled degradations to audio: e.g. data augmentation, evaluation in noisy conditions, etc.
Luncz allows musicians to record a 10 second snippet of live music played on an acoustic or an amplified instrument, and analyzes the recording to extract the notes, the tempo, and the intensity level of the music. Using this data, Luncz generates new music to accompany the musician.