This module defines detctors for identifying sounds in sound clips. Detectors are defined, with each detector returning a numerical score that may subsequently be used to classify the clip by whether or not it contains a particular sound.
This is a python project
- Get the code
git clone git://github.com/dragonfly-science/kokako.git - Install the dependencies (numpy, matplotlib)
- Change to the
kokakodirectory - Run
python setup.py install
kokako --help
Provides help on how to use kokako
kokako --list
List available detectors
kokako <detector name> [<detector version>] [-o <filename>] <path>
Score sound files. To score a file specify which detector to use (), an optional version (),
and a path (). If path is a wav file then kokako will return a single score. If path is a directory, then kokako
will recursively walk that directory scoring all the wav files that it finds.
You are welcome to contrbute better detectors, or detectors for the sound that you would like to identify. Please fork the code on github.
Kokako is used by the songscape project (http://www.songscape.org), which aims to use machine learning to analyse sounds in large volumes of sound data.
Copyright (C) 2013 Dragonfly Science
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.