Search Results for "machine learning platform"
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Showing 7 open source projects for "machine learning platform"
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jMIR
Music research software
...It also includes tools for managing and profiling large music collections and for checking audio for production errors. jMIR includes software for extracting features, applying machine learning algorithms, applying heuristic error error checkers, mining metadata and analyzing metadata. -
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SynthePG
Live Music Compositor learning base on TPG
This android app is producing music and partition sheets in real time. Furthermore, the AI module can be activated and be trained to learn you prefered style and play it. You can also team play your music with the interconnect mode. Finally, move your phone like a 'chef d'orchestre' and see how it changes the music... -
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Bermuda Text-to-Speech
This project includes basic NLP and DSP techniques for Text-to-Speech
See TTS demo at: http://rslp.racai.ro/index.php?page=tts This is an entirely written in JAVA project which includes a set of tools and methods designed to enable Multilingual Text-to-Speech (TTS) synthesis. We currently support English and Romanian but we will soon train more models and make them available for download. If you want to read more about our other NLP and TTS tools check out http://nlptools.racai.ro. -
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Mantra Machine is an emulation of the Buddha Machine hardware, a small box that endlessly plays ambient loops. In this release you will find the original loops of the hardware plus an exclusive set of sounds. Two versions: Java Edition and Linux Qt.
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An experimental unsupervised learning method for improvising jazz melodies, based on restricted Boltzmann machines (RBMs) layered into Deep Belief Networks (forms of neural networks).
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VBox/J is a platform independent Java application for controlling a 'vboxd' answering machine. Vboxd (not VBox/J) is part of the isdn4linux project.
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TigerBeats' project goal is to create a drum machine for the Android platform that is file compatible with the excellent Hydrogen application while fully embracing the look, feel, and limitations of the platform.
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