nbest-mix
reads a number of N-best lists (which must contain identical
hypotheses), computes the hypothesis posterior probabilities for each,
and computes a new posterior distribution that is a
weighted mixture of the input distributions.
The hypothesis with the highest combined posterior probability is
printed.
The command line arguments form an alternating list of
weight values and N-best file names.
OPTIONS
-help
Print option summary.
-debug level
Controls the amount of output (the higher the
level,
the more).
-write-nbest file
Outputs the N-best list corresponding to the interpolated
posterior distribution to a file.
This suppresses the printing of the best hyp.
-max-nbest n
Limits the number of hypotheses read from each N-best list to the first
n.
-rescore-lmw lmw
Sets the language model weight used in combining the language model log
probabilities with acoustic log probabilities
(only relevant if separate scores are given in the N-best input).
-rescore-wtw wtw
Sets the word transition weight used to weight the number of words relative to
the acoustic log probabilities
(only relevant if separate scores are given in the N-best input).
-posterior-scale scale
Divide the total weighted log score by
scale
when computing normalized posterior probabilities.
This controls the peakedness of the posterior distribution.
The default value is whatever was chosen for
lmw,
so that language model scores are scaled to have weight 1,
and acoustic scores have weight 1/lmw.