This package is part of the ALIZÉ project: http://alize.univ-avignon.fr
LIA_RAL is a set of utilities for Automatic Speaker Recognition developed at LIA, providing a high-level access to the ALIZÉ platform. All these utilities are based on the core ALIZE
library, which is required in order to compile LIA_RAL.
LIA_RAL is an open project. Feel free to contact us to propose to work on it!
In order to use Support Vector Machines, the libsvm
library is included in this package. For more information on libsvm
, please refer to:
http://www.csie.ntu.edu.tw/~cjlin/libsvm/
The Eigen
library is also included into this package. For more information on Eigen
, please refer to:
http://eigen.tuxfamily.org
aclocal
, autoconf
, automake
and libtool
are required.
This package also requires the core ALIZE
library.
Follow these four steps:
- Install the
ALIZE
library. - Run, in this order:
aclocal
automake
autoconf
- Then run
./configure
. By default, theALIZE
library is searched for in../alize-core
. It may be in a folder with a different name, depending on how you downloaded the library, or if you have decided to install it in a non-default location. If so, you can specify the absolute path by using the--with-alize=ABSOLUTE_PATH
option. - Finally, run
make
.
Note: At step 2, you may need to use automake --add-missing
if the file compile
cannot be found.
Use the LIA_RAL.sln
solution file. If your version of Visual Studio is newer than 2010, you just have to convert it using Visual studio tools.
Please read this technote: http://alize.univ-avignon.fr/mediawiki/index.php/Main_Page
In a shell, in the main folder of LIA_RAL:
doxygen doxygen.cfg
Of course, you need to have doxygen
installed.
Run ./configure
with the option --enable-MT
.
Install LapackE
then run ./configure
with the option --enable-LAPACK
.
LIA_RAL includes a class (LIA_SpkDet/SimpleSpkDetSystem
) which exposes a high-level API for a speaker verification/identification system, completely masking the details of how to implement such a system with ALIZÉ. This API targets application developers who want an easy way to embed speaker recognition in their applications, without having to learn all the details of speaker recognition.
The system can be fed features, in order to train models and run tests. But in its intended use as part of an application, it will be directly given an audio signal, which it will parameterize. In order to do this, the system must be compiled with a link to the SPro library, which will handle parameterization.
After downloading SPro 5 (https://gforge.inria.fr/projects/spro/), compile it according to the instructions in the package.
If you are only going to use SPro for the purpose of linking LIA_RAL with its library, there is no need to make install
after compiling it. The compiled version can just stay in the distribution directory. If you install SPro somewhere else (by default, it installs in /usr/local/
), then you need to copy the system.h
file from the SPro distribution directory into the SPro include
installation directory, since this file is needed for the compilation of SpkDetServer
but not copied there by the SPro installation process.
Finally, use the --with-spro
option when running configure
for LIA_RAL. By default, it will look for SPro in ../spro
. You can specify a different path if required (--with-spro=path
).
The high-level speaker recognition API can be used with a local instance, in C++ (using LIA_SpkDet/SimpleSpkDetSystem
) or in Java for Android applications (using the code found in the Android-ALIZÉ
repository, which adds a JNI/Java layer over this class).
It is also usable over the network in a client/server mode (using the code in LIA_SpkDet/RemoteSpkDet
). Along with a speaker detection server, an example of a client is included. It is compiled with the rest of LIA_RAL, but it does not link with the ALIZE
and LIA_RAL
libraries and can be compiled completely independently.
For more information please refer to: http://alize.univ-avignon.fr/mediawiki/index.php/Main_Page