203 lines
6.1 KiB
Groff
203 lines
6.1 KiB
Groff
.\" $Id: segment-nbest.1,v 1.10 2019/09/09 22:35:37 stolcke Exp $
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.TH segment-nbest 1 "$Date: 2019/09/09 22:35:37 $" "SRILM Tools"
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.SH NAME
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segment-nbest \- rescore and segment N-best lists using hidden segment N-gram model
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.SH SYNOPSIS
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.nf
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\fsegment-nbest\fP [ \fB\-help\fP ] \fIoption\fP ... \fInbest-file-list\fP ...
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.fi
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.SH DESCRIPTION
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.B segment-nbest
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processes a series of consecutive N-best lists from a speech
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recognizer
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and applies a hidden segment N-gram language model to them.
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The language model is a standard backoff N-gram model in ARPA
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.BR ngram-format (5)
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modeling sentence segmentation using the boundary tags <s> and </s>.
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The program reads in all N-best lists and outputs the
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hypotheses that have the highest aggregate (combined acoustic
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and language model) score.
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Hypothesized sentence boundaries are marked by <s> tags.
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.SH OPTIONS
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.PP
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Each filename argument can be an ASCII file, or a
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compressed file (name ending in .Z or .gz), or ``-'' to indicate
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stdin/stdout.
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.TP
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.B \-help
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Print option summary.
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.TP
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.B \-version
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Print version information.
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.TP
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.BI \-order " n"
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Set the maximal N-gram order to be used, by default 3.
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NOTE: The order of the model is not set automatically when a model
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file is read, so the same file can be used at various orders.
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.TP
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.BI \-debug " level"
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Set the debugging output level (0 means no debugging output).
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Debugging messages are sent to stderr.
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.TP
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.BI \-lm " file"
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Read the N-gram model from
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.IR file .
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.TP
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.B \-tolower
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Map all vocabulary to lowercase.
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Useful if case conventions for N-best lists and language model differ.
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.TP
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.BI \-mix-lm " file"
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Read a second, standard N-gram model for interpolation purposes.
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.TP
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.BI \-lambda " weight"
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Set the weight of the main model when interpolating with
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.BR \-mix-lm .
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Default value is 0.5.
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.TP
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.BI \-bayes " length"
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Interpolate the second and the main model using posterior probabilities
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for local N-gram-contexts of length
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.IR length .
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The
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.B \-lambda
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value is used as a prior mixture weight in this case.
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.TP
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.BI \-bayes-scale " scale"
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Set the exponential scale factor on the context likelihood in conjunction
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with the
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.B \-bayes
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function.
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Default value is 1.0.
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.TP
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.BI \-nbest-files " list"
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Specifies a list of N-best files.
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The file
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.I list
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should contain a list of filenames, one per line,
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each corresponding to an N-best file in one of the formats
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described in
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.BR nbest-format (5).
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The N-best files should correspond to consecutive speech waveforms
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in the order listed.
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.TP
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.B \-fb-rescore
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Perform Forward-backward rescoring.
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This generates new N-best lists
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as output whose LM scores reflect the posterior probability of each
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hypothesis.
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The default is to perform Viterbi rescoring and output only the
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best combined hypothesis.
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.TP
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.BI \-write-nbest-dir " dir"
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Write rescored N-best lists to directory
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.I dir
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instead of to stdout.
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The filenames from the input are preserved.
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.TP
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.BI \-max-nbest " n"
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Limits the number of hypotheses read from each N-best list to the first
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.IR n .
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.TP
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.BI \-max-rescore " m"
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Only choose among the top
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.I m
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hypotheses of each list (after reordering hypotheses, see below).
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This is an effective way to limit the quadratic computation
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of the Viterbi or forward/backward dynamic programming.
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.TP
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.B \-no-reorder
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Do not reorder the hypotheses before limiting the computation to
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the top
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.IR m .
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By default the hypotheses will first be sorted according to the
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acoustic and language model scores recorded in the N-best lists.
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.TP
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.BI \-rescore-lmw " weight"
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Specifies the language model weight to be use in combining
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acoustic and language model scores to select the best hypotheses.
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.TP
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.BI \-rescore-wtw " weight"
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Specifies the word transition weight to be used in selecting the
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best hypotheses.
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.TP
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.BI \-noise " noise-tag"
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Designate
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.I noise-tag
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as a vocabulary item that is to be ignored by the LM.
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(This is typically used to identify a noise marker.)
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.TP
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.BI \-noise-vocab " file"
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Read several noise tags from
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.IR file ,
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instead of, or in addition to, the single noise tag specified by
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.BR \-noise .
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.TP
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.BI \-decipher-lm " model-file"
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Designates the N-gram backoff model (typically a bigram) that was used by the
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Decipher(TM) recognizer in computing composite scores.
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Used to compute acoustic scores from the composite scores if the
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N-best lists are in "NBestList1.0" format.
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.TP
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.BI \-decipher-lmw " weight"
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Specifies the language model weight used by the recognizer.
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Used to compute acoustic scores from the composite scores.
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.TP
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.BI \-decipher-wtw " weight"
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Specifies the word transition weight used by the recognizer.
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Used to compute acoustic scores from the composite scores.
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.TP
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.BI \-stag " string"
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Use
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.I string
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to mark segment boundaries in the output.
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Default is the start-of-sentence symbol defined in the language model (<s>).
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.TP
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.BI \-bias " b"
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Make a segment boundary a priori more likely by a factor of
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.IR b .
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If
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.I b
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is 0, the dynamic program algorithm is restricted to never consider
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hidden sentence boundaries; this is useful when
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.B segment-nbest
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is used merely for its ability to apply the LM across N-best boundaries.
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.TP
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.BI \-start-tag " string"
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Insert a tag
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.I string
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at the front of every N-best hypothesis read in.
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.TP
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.BI \-end-tag " string"
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Insert a tag
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.I string
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at the end of every N-best hypothesis read in.
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This and the previous option are useful if the LM marks acoustic
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waveform boundaries with a special tag.
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.PP
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.B segment-nbest
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will also process any command line arguments following the options
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as lists of N-best lists, as with the
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.B \-nbest-files
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option.
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Each
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.I nbest-file-list
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will be processed in turn,
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with individual output delimited by a line of the form
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.nf
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<nbestfile \fInbest-file-list\fP>
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.fi
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.SH "SEE ALSO"
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ngram-count(1), segment(1), ngram-format(5), nbest-format(5).
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.br
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A. Stolcke, ``Modeling Linguistic Segment and Turn Boundaries for N-best
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Rescoring of Spontaneous Speech,'' \fIProc. Eurospeech\fP, 2779\-2782, 1997.
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.SH BUGS
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N-gram models of arbitrary order can be used, but the context at the
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beginning of a hypothesis never extends beyond the words from the preceding
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N-best list.
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.SH AUTHOR
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Andreas Stolcke <stolcke@icsi.berkeley.edu>
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.br
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Copyright (c) 1997\-2004 SRI International
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