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src/doc/tutorial_prereqs.dox 3.76 KB
8dcb6dfcb   Yannick Estève   first commit
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  // doc/tutorial_prereqs.dox
  
  // Copyright 2009-2011 Microsoft Corporation
  
  // See ../../COPYING for clarification regarding multiple authors
  //
  // Licensed under the Apache License, Version 2.0 (the "License");
  // you may not use this file except in compliance with the License.
  // You may obtain a copy of the License at
  
  //  http://www.apache.org/licenses/LICENSE-2.0
  
  // THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  // KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
  // WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
  // MERCHANTABLITY OR NON-INFRINGEMENT.
  // See the Apache 2 License for the specific language governing permissions and
  // limitations under the License.
  
  /**
   \page tutorial_prereqs Kaldi tutorial: Prerequisites
  
     \ref tutorial "Up: Kaldi tutorial" <BR>
     \ref tutorial_setup "Next: Getting started" <BR>
  
    This tutorial assumes that you know the basics of speech recognition using the
    HMM-GMM approach.  One brief introduction that is available online
    is: M. Gales and S. Young (2007). ``The Application of Hidden Markov
    Models in Speech Recognition." Foundations and Trends in Signal Processing
    1(3): 195-304.  The HTK Book is also a good resource.  However, unless you
    have a strong mathematical background and are extremely dedicated, we
    discourage trying to learn about speech recognition outside an institutional
    setting.  The intended audience for this tutorial is either speech recognition
    researchers, or graduates or advanced undergraduates who are studying this
    area anyway.
  
    We assume that you know C++, and have at least some familiarity with shell
    scripting, preferably using bash or a similar shell.  This tutorial assumes you
    are using a UNIX-like environment or Cygwin (although Kaldi will not
    necessarily compile and run in all such environments).
  
    Also, importantly, the tutorial assumes you have access to the data on the Resource
    Management (RM) CDs from the Linguistic Data Consortium (LDC), in the original form
    as distributed by the LDC.  That is, we assume this data is sitting on your system
    somewhere.  We obtained this as catalog number LDC93S3A.   It is
    also available in two separate pieces.  Be careful because there was previously
    a different distribution of the RM data with a different layout.
  
    The system requirements are fairly basic.  We assume that you have tools
    including wget, git, svn, awk, perl and so on, or that you know how to install them.
    The most difficult part of the installation process relates to the math library
    ATLAS; if this is not already installed as a library on your system you will
    have to compile it, and this requires that CPU throttling be turned off, which
    may require root privileges.  We provide scripts and detailed instructions for
    all installation steps.  When scripts fail, read the output carefully because
    it tries to provide guidance as to how to fix problems.  Please inform us if there
    are problems at any point, however minor; see \ref other.
  
    We try to provide some idea how long it should take to execute each step of the tutorial.
    If there is a limited amount of time available to complete the tutorial, we recommend
    to try to keep to the posted schedule, if necessary by skipping steps and avoiding
    following links to more information that we provide in the text.  This will help ensure
    that you get a balanced overview.  You can always review the material in more
    detail later on.  If this tutorial is to be given in a classroom setting, it is
    important that someone run through the tutorial on the relevant system beforehand in order
    to verify that all the prerequisites are installed.
  
     \ref tutorial "Up: Kaldi tutorial" <BR>
     \ref tutorial_setup "Next: Getting started" <BR>
  <P>
  */