ALIZÉ is an opensource platform for speaker recognition. The purpose of this project is to provide a set of low-level and high-level frameworks that will allow anybody to develop applications handling the various tasks in the field of speaker recognition: verification/identification, segmenting, etc.
In order to better suit everybody’s needs, ALIZÉ was developed with a multi-layer architecture.
The base layer is ALIZE-Core, a low-level library which includes all the functions required to use Gaussian mixtures, as well as I/O functions for various file formats.
On top of this core was built LIA_RAL, a toolkit offering higher-level functionnality. LIA_RAL is itself made of several components:
This software was developed with multi-platform compatibility in mind. It has been tested and used on Linux, Windows, and Mac OS. It should also be usable on any POSIX-compliant operating system.
Efforts are underway to make it easier to integrate ALIZÉ into mobile applications.
The source code of ALIZÉ is available on GitHub at this address: https://github.com/ALIZE-Speaker-Recognition.
The source code of ALIZÉ (both ALIZE-Core and LIA_RAL) is released under the terms of the GNU Lesser General Public License (LGPL).
Unfortunately, the documentation for the library APIs is in dire need of an update, and is not therefore available for the current version of ALIZÉ.
Several tutorials are available to get you started with the tools LIA_SpkDet and LIA_SpkSeg.
Tutorial for LIA_SpkDet — GMM/UBM System
Tutorial for LIA_SpkDet — I-vector System
Tutorial for LIA_SpkDet — JFA System
Tutorial for LIA_SpkSeg — Top-down Speaker Segmenting and Clustering System
Since the launch of the project in 2005, ALIZÉ has attracted a rich community of users and developers.
The best way to exchange with the community is through the dev-alize mailing list:
The community may also be reached through the ALIZÉ group on LinkedIn.
Follow this link to see a list of scientific papers related to ALIZÉ and its use for research in speaker recognition.
ALIZÉ is opensource software. If you want to extend it or submit bug fixes, do not hesitate to join the community and help us maintain a state-of-the-art speaker recognition toolkit.
Of course, there are also other ways you can contribute:
Feel free to join the effort! :-)