ppl-scripts.1

这是一款很好用的工具包

.\" $Id: ppl-scripts.1,v 1.3 2002/04/19 14:11:30 stolcke Exp $
.TH ppl-scripts 1 "$Date: 2002/04/19 14:11:30 $" "SRILM Tools"
.SH NAME
ppl-scripts, add-ppls, compare-ppls, compute-best-mix, compute-best-sentence-mix, hits-from-log, ppl-from-log, subtract-ppls \- manipulate perplexities
.SH SYNOPSIS
.B add-ppls 
.RI [ ppl-file ..]
.br
.B subtract-ppls
.I ppl-file1
.RI [ ppl-file2 ...]
.br
.B ppl-from-log
.RI [ ppl-file ...]
.br
.B hits-from-log
.RI [ ppl-file ...]
.br
.B compare-ppls 
[\c
.BI mindelta= D\c
]
.I ppl-file1
.I ppl-file2
.br
.B compute-best-mix
[\c
.BI lambda=' "l1 l2"
.RB ... '
.BI precision= P\c
]
.I ppl-file1
.RI [ ppl-file2 ...]
.br
.B compute-best-sentence-mix
[\c
.BI lambda=' "l1 l2"
.RB ... '
.BI precision= P\c
]
.I ppl-file1
.RI [ ppl-file2 ...]
.SH DESCRIPTION
These scripts process the output of the 
.BR ngram (1)
option
.B \-ppl
to extract various useful information.
They are particularly convenient in analyzing the performance (perplexity) of 
language models on specific subsets of the test data,
or to compare and combine multiple models.
.PP
.B add-ppls 
takes several ppl output files and computes an aggregate perplexity and
corpus statistics.
Its output is suitable for subsequent manipulation by
.B add-ppls 
or
.BR subtract-ppls .
.PP
.B subtract-ppls
similarly computes an aggregate perplexity by removing the
statistics of zero or more
.I ppl-file2
from those in
.IR ppl-file1 .
Its output is suitable for subsequent manipulation by
.B add-ppls 
or
.BR subtract-ppls .
.PP
.B ppl-from-log
recomputes the total perplexities and statistics from individual
lines in
.B "ngram \-debug 2 \-ppl"
output.
Combined with some filtering of that output this allows computing 
perplexities on interesting subsets of words.
.PP
.B hits-from-log
computes N-gram hit rates from
.B "ngram \-debug 2 \-ppl"
output.
.PP
.B compare-ppls
tallies the number of words for which two language models produce the same,
higher, or lower probabilities.
The input files should be 
.B "ngram \-debug 2 \-ppl"
output for the two models on the same test set.
The parameter
.I D
is the minimum absolute difference for two log probabilities to be 
considered different (the default is 0).
.PP
.B compute-best-mix
takes the output of several
.B "ngram \-debug 2 \-ppl"
runs on the same test set and computes the optimal interpolation 
weights for the corresponding models,
i.e., the weights that minimize the perplexity of an interpolated model.
Initial weights may be specified as
.IR "l1 l2 ..." .
The computation is iterative and stops when the interpolation weights
change by less than
.I P 
(default 0.001).
.PP
.B compute-best-sentence-mix
similarly optimizes the weights for sentence-level interpolation of LMs.
It requires input files generated by
.BR "ngram \-debug 1 \-ppl" .
(Sentence-level mixtures can be implemented using the 
.B "ngram \-hmm"
option, by constructing a suitable HMM structure.)
.SH "SEE ALSO"
ngram(1).
.SH BUGS
All scripts depend on the idiosyncrasies of
.B "ngram \-ppl" 
output.
.SH AUTHOR
Andreas Stolcke <[e-mail]>.
.br
Copyright 1995-2002 SRI International