CS4706 Spring 2012
PocketSphinx is an open-source toolkit for speech recognition from
Carnegie Mellon University. It's cross-platform, and has built-in
language and acoustic models, but you can also use and train your
own. You will be using PocketSphinx as the recognizer for your term
projects. You can use the lab machines or your own personal computers
for the projects. If you choose to work on your own computer,
instructions for getting set up with PocketSphinx can be found below:
The Python example from the setup instructions shows how to use both
the default n-gram language model that was trained on the Wall Street
Journal (the commented-out decoder), as well as an example of a custom
JSGF grammar and pronunciation dictionary, which is what you will be
designing as part of your project.
The PocketSphinx website has extensive documentation, as well as a
help forum for questions.
Please note that while we are providing these instructions for getting
PocketSphinx set up on your own computer, we will not be able to
provide extensive debugging support for your installation, due to
variations in everyone's individual settings and configurations. Please also note that
even if you work on your own computer, you are still responsible for
making sure that your project runs on the lab machines.