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Sphinxtrain --------------------------------- This is SphinxTrain, Carnegie Mellon University's open source acoustic model trainer. This directory contains the scripts and instructions necessary for building models for the CMU Sphinx Recognizer. This distribution is free software, see LICENSE for licence. For up-to-date information, please see the web site at http://cmusphinx.sourceforge.net Among the interesting resources there, you will find a link to "Resources to build a recognition system", with pointers to a dictionary, audio data, acoustic model etc. For introduction in training the acoustic model see the tutorial http://cmusphinx.sourceforge.net/wiki/tutorialam Installation Guide: ============================================================================== This sections contain installation guide for various platforms. All Platforms: ============================================================================== You will need Perl to use the scripts provided. Linux usually comes with some version of Perl. If you do not have Perl installed, please check: http://www.perl.org where you can download it for free. For Windows, a popular version, ActivePerl, is available from ActiveState at: http://www.activestate.com/Products/ActivePerl/ For some advanced techniques (which are not enabled by default) you will need Python with NumPy and SciPy. Python can be obtained from: http://www.python.org/download/ Packages for NumPy and SciPy can be obtained from: http://scipy.org/Download Linux/Unix Installation: ============================================================================== This distribution now uses GNU autoconf to find out basic information about your system, and should compile on most Unix and Unix-like systems, and certainly on Linux. To build, simply run ./configure make make install This should configure everything automatically. The code has been tested with gcc. Also, check the section title "All Platforms" above. Windows Installation: ============================================================================== First, you *must* have SphinxBase, which you can download from http://cmusphinx.sourceforge.net/. You should download and unpack it to the same parent directory as PocketSphinx, so that the configure script and project files can find it. On Windows, you will need to rename 'sphinxbase-X.Y' (where X.Y is the SphinxBase version number) to simply 'sphinxbase' for this to work. To compile the SphinxTrain under MS Visual Studio 2010 (or newer - we test with Visual C++ 2010 Express): 1. load SphinxTrain.sln located in SphinxTrain directory 2. compile all the projects in SphinxTrain (from SphinxTrain.sln) MS Visual Studio will build the executables under .\bin\Release or .\bin\Debug (depending on the version you choose on MS Visual Studio), and the libraries under .\lib\Release or .\lib\Build. If you are using cygwin, the installation procedure is very similar to the Unix installation. Also, check the section title "All Platforms" above. Once you finished with compilation, copy the pocketsphinx and sphinxbase tools and dlls from sphinxbase\bin\Releae and pocketsphinx\bin\Release to sphinxtrain\bin\Release folder. This will enable you to run the training process which expects to see all the tools and libraries in sphinxtrain\bin\Release. Acknowldegments ============================================================================== The development of this code has included support at different times by various United States Government agencies, under different programs, including the Defence Advanced Projects Agency (DARPA) and the National Science Foundation (NSF). We are grateful for their support. This work was built over a large number of years at CMU by most of the people in the Sphinx Group. Some code goes back to 1986. The most recent work in tidying this up for release includes the following, listed alphabetically (at least these are the people who are most likely able to help you). Alan W Black ([email protected]) Arthur Chan ([email protected]) Evandro Gouvea ([email protected]) Ricky Houghton ([email protected]) David Huggins-Daines ([email protected]) Kevin Lenzo ([email protected]) Ravi Mosur Long Qin ([email protected]) Rita Singh ([email protected]) Eric Thayer
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