Search Results for "artificial intelligence algorithm"

jMIR is an open-source software suite implemented in Java for use in music information retrieval (MIR) research. It can be used to study music in the form of audio recordings, symbolic encodings and lyrical transcriptions, and can also mine cultural information from the Internet. 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...

MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.

Diglo is a Music Information Retrieval System based on Computer Vision and Audio Spectrum Analysis, using algorithmic operations to find emergent patterns in musical performance. Also it functions as a low-cost Motion Capture Analysis system.

Easy-to-use platform-independent plugin API for the extraction of low-level features from audio data in PCM format, as required in the context of music information retrieval software.

Segfried is an audio feature extraction and segmentation utility

Instant Bach is a program that uses artificial intelligence to do four-part harmony writing, with or without a user specified progression, according to all the rules of four-part harmony writing, and has the ability to transpose the result into any key.

TSSBank is written in c#(.Net 2.0).The main aimed group is the disabled persons.This component outputs voice & textual outputs (with value/words)plus experimental Voice Recognition (VR) system that identifies more then 80% accurately with out training.

musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.

Evomusic deals with automatic composition of music (midi-files) using evolutionary algorithms. Currently we are testing multiple approaches for doing this successfully, especially neural networks and/or algorithms based on simple music theory.

Mixing Bhatkhande rules with Traditional and Learning based software techniques to classify of existing as well as predicting new North Indian (Hindustani) Classical Music raaga\'s (raga\'s)