TRANSLATOR

You need apertium-1.0 and lttoolbox-1.0 to use this translator.  To compile
the linguistical data simply do:

make

inside of this directory.

TAGGER 

To use this language-pair package with apertium YOU DO NOT NEED TO
RETRAIN THE TAGGER. Probabilities and auxiliary data are provided for
both the ca-es and the es-ca translation directions which should be
acceptable for most applications, and should work even if you change
the dictionaries in a reasonably way.

If for some reason you need to retrain the tagger (for example, you
have made really extensive changes to the dictionaries such as
creating new lexical categories), you have two alternatives:

* To perform a supervised training:

  To this end tagged corpora is provided, but tagged corpora
  (es-tagger-data/es.tagged and ca-tagger-data/ca.tagged) could be
  obsolete for some words. If this is the case, the tagger training 
  program  will show you where the problems are and you will need 
  to solve them by hand. Be sure to solve the problems by modifying 
  ONLY the .tagged file, NEVER the .untagged file that is 
  automatically generated.

  The supervised training is done by typing: make tagger_supervised

* To perform an unsupervised training:

  For this purpose you will need to assemble a large (hundreds of
  thousand of words) plain-text corpus for each language (for example,
  using a robot to harvest text from online newspapers) and put them in
  the proper place, for instance es-tagger-data/es.crp.txt and
  ca-tagger-data/ca.crp.txt. This type of training does not need human
  intervention but, as expected, results will be less adequate than
  those obtained with the supervised training.

  The unsupervised training is done through the iterative Baum-Welch
  algorithm. By default the number of iterations is set to 8, but you
  can change this value by editing the Makefile and changing the
  value of TAGGER_UNSUPERVISED_ITERATIONS.

  The unsupervised training is done by typing: make tagger_unsupervised
