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PocketSphinx is a lightweight speech recognition engine, specifically tuned for handheld and mobile devices, though it works equally well on the desktop

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PocketSphinx 5prealpha

This is PocketSphinx, one of Carnegie Mellon University's open source large vocabulary, speaker-independent continuous speech recognition engine.

THIS IS A RESEARCH SYSTEM. This is also an early release of a research system. We know the APIs and function names are likely to change, and that several tools need to be made available to make this all complete. With your help and contributions, this can progress in response to the needs and patches provided.

Please see the LICENSE file for terms of use.

Prerequisites

You must have SphinxBase, which you can download from http://cmusphinx.sourceforge.net. 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.

Linux/Unix installation

In a unix-like environment (such as linux, solaris etc):

  • Build and optionally install SphinxBase. If you want to use fixed-point arithmetic, you must configure SphinxBase with the --enable-fixed option.

  • If you downloaded directly from the CVS repository, you need to do this at least once to generate the "configure" file:

    $ ./autogen.sh
    
  • If you downloaded the release version, or ran autogen.sh at least once, then compile and install:

    $ ./configure
    $ make clean all
    $ make check
    $ sudo make install
    

Xcode Installation (for iPhone)

Pocketsphinx uses the standard unix autogen system, you can build pocketsphinx with automake given you already built sphinxbase You just need to pass correct configure arguments, set compiler path, set sysroot and other options. After you build the code you need to import dylib file into your project and you also need to configure includes for your project to find sphinxbase headers.

You also will have to create a recorder to capture audio with CoreAudio and feed it into the recognizer.

For details see http://github.com/cmusphinx/pocketsphinx-ios-demo

If you want to quickly start with Pocketsphinx, try OpenEars toolkit which includes Pocketsphinx http://www.politepix.com/openears/

Android installation

See http://github.com/cmusphinx/pocketsphinx-android-demo.

MS Windows™ (MS Visual Studio 2012 (or newer - we test with VC++ 2012 Express)

  • load sphinxbase.sln located in sphinxbase directory

  • compile all the projects in SphinxBase (from sphinxbase.sln)

  • load pocketsphinx.sln in pocketsphinx directory

  • compile all the projects in PocketSphinx

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.

Test scripts are forthcoming for Windows.

For up-to-date information, see http://cmusphinx.sourceforge.net.

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PocketSphinx is a lightweight speech recognition engine, specifically tuned for handheld and mobile devices, though it works equally well on the desktop

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