Festival Speech Synthesis System: - Speech Resource Pages

(define (pos_cand_function w)
;; select the appropriate lexicon
(lex.select 'pos_lex)
;; return the list of cands with rprobs
(cadr
(lex.lookup (item.name w) nil)))
The returned candidate list would look somthing like
( (jj -9.872) (vbd -6.284) (vbn -5.565) )
Our part of speech tagger function would look something like this
(define (pos_tagger utt)
(set! get_vit_params
(list
(list 'Relation "Word")
(list 'return_feat 'pos_tag)
(list 'p_word "punc")
(list 'pp_word "nn")
(list 'ngramname "pos-tri-gram")
(list 'cand_function 'pos_cand_function)))
(Gen_Viterbi utt)
utt)
this will assign the optimal part of speech tags to each word in utt.
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25.5 Linear regression
The linear regression model takes models built from some external package and finds coefficients based on the
features and weights. A model consists of a list of features. The first should be the atom Intercept plus a value.
The following in the list should consist of a feature (see section 14.6 Features) followed by a weight. An optional
third element may be a list of atomic values. If the result of the feature is a member of this list the feature's value is
treated as 1 else it is 0. This third argument allows an efficient way to map categorical values into numeric values.
For example, from the F0 prediction model in `lib/f2bf0lr.scm'. The first few parameters are
(set! f2b_f0_lr_start
'(
( Intercept 160.584956 )
( Word.Token.EMPH 36.0 )
( pp.tobi_accent 10.081770 (H*) )
( pp.tobi_accent 3.358613 (!H*) )
( pp.tobi_accent 4.144342 (*? X*? H*!H* * L+H* L+!H*) )
( pp.tobi_accent -1.111794 (L*) )
...
)
Note the feature pp.tobi_accent returns an atom, and is hence tested with the map groups specified as third
arguments.
Models may be built from feature data (in the same format as `wagon' using the `ols' program distributed with
the speech tools library.
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