Open Source Java Audio Analysis Software - Page 4

Software provides two features, 1. To identify the musical notes in a given audio file which the singer is singing at. 2. To let a user practice singing individual notes of Indian music, with graphical representation of his performance.

A visualization of the fourier transform applied to sound data. Analyzes a time-domain sound sample using the Fourier Transform, and graphically displays the results and sound in real time. Attempts to audio into sheet music.

A simple Java GUI tool for looking at the Spectrum and Cepstrum of a sound clip.

The concept of Computer Aided Music Composition emerged as a natural sequel to the music hardware/software revolution dating back to early 50s. STOCASTICVS aims to grow into the best CAMC software yet, truly unleashing individual’s creative potential.

Simple program to assist transcriptions from recorded interviews. Resembles somewhat the early F4. <br/>Keywords: transcription transcribe interview

The basic function is to allow the user to take notes while watching a computer video file. The program combines a video playback window and a very simple text editor. Keyboard shortcuts can control playback, e.g. pause/resume, skip back, etc. MacOS Yosemite Problems - the latest version of MacOS has removed the QuickTimeForJava libraries on which this tool relies. If you copy the appropriate files from a Mavericks installation, it will work again. The files you will need to copy from Mavericks to Yosemite are: /System/Library/QuickTimeJava to the same location /System/Library/Java/Extensions/QTJava.zip to /System/Library/Java/JavaVirtualMachines/1.6.0.jdk/Contents/Home/lib/ext Also download the latest version, the only change of which is to ask for Java 1.6.

VisualAp is a visual framework for building application and systems based on visual components. Users can add their own visual components in order to extend the capability of VisualAp. Tested with Windows XP, Vista, 7 and Ubuntu.

A guitar tuner written in Java, comparing frequencies detected in the signal from the microphone to standard or user-defined notes. The number of notes tested and their frequency is configurable, so it can be used for other instruments and other tunings.

compariSong is an audio tool to support query by singing/humming. It compares a database of popular songs with a hummed-by-user melody and returns the closest matches.

Repackaged what was needed to use jAudioTagger as a library in Java. Made it usable as a netbeans project. Added targets in the build.xml to produce sources jar and javadocs jar for the library jar that is produced. Also uploaded are those jars (that I couldn't find anywhere else).

This library is a Java port from the libFooID audio fingerprinting library created by Gian-Carlo Pascutto. The fingerprint captures how the audio is perceived by an audience so it can e.g. be used in a database to retrieve metatags of a track.

This project is to provide a MusicBrainz Tagging application written in Java so it is cross platform.

A playlist copy-tool written in Java.

Goal of this project is to develop a piece of java-based software for handling of music files. The program identifies the provided music files using several techniques, retrieves the matching metadata from the internet and updates the file.

trubadix, *the* data sonifier for great music

Creates universal playlists in XML. These can be exported to most music player's playlist format like winamp, realplayer, jukebox or any music player of your choice. Supports ID3, Searching & Indexing songs. XML data for easy retrieval & readability.

AcMus is a project on musical acoustics devoted to the development of models and computer tools for the study of room acoustics and focus on helping the investigation of issues related to the design, control and acoustic treatment of environments. AcMus has not been maintained for a few years now, but the code may still be useful. We consider the current repository to be at https://gitlab.com/ccsl-usp/acmus .

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.