There are two methods for predicting phrase breaks in Festival, one
simple and one sophisticated. These two methods are selected through
Phrase_Method and phrasing is achieved by the
The first method is by CART tree. If parameter
cart_tree, the CART tree in the variable
is applied to each word to see if a break should be inserted or not.
The tree should predict categories
BB (for big break),
(for break) or
NB (for no break). A simple example of a tree to
predict phrase breaks is given in the file `lib/phrase.scm'.
(set! simple_phrase_cart_tree ' ((R:Token.parent.punc in ("?" "." ":")) ((BB)) ((R:Token.parent.punc in ("'" "\"" "," ";")) ((B)) ((n.name is 0) ((BB)) ((NB))))))
The second and more elaborate method of phrase break prediction is used
when the parameter
prob_models. In this
case a probabilistic model using probabilities of a break after a word
based on the part of speech of the neighbouring words and the previous
word. This is combined with a ngram model of the distribution of breaks
and non-breaks using a Viterbi decoder to find the optimal phrasing of
the utterance. The results using this technique are good and even show
good results on unseen data from other researchers' phrase break tests
(see black97b). However sometimes it does sound wrong,
suggesting there is still further work required.
Parameters for this module are set through the feature list held
in the variable
phr_break_params, and example of which
for English is set in
the file `lib/phrase.scm'. The features names and meaning are
posfeature of words into a smaller tagset used by the phrase predictor.
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