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<! $Id: segment.1,v 1.6 2004/12/03 17:59:01 stolcke Exp $><HTML><HEADER><TITLE>segment</TITLE><BODY><H1>segment</H1><H2> NAME </H2>segment - segment text using N-gram language model<H2> SYNOPSIS </H2><B> segment </B>[<B>-help</B>]<B></B>option...<H2> DESCRIPTION </H2><B> segment </B>infers a most likely segmentation (location of segment boundaries)from a text, based on a segment language model.The language model is a standard backoff N-gram model in ARPA<A HREF="ngram-format.html">ngram-format(5)</A>,modeling segmentation using the boundary tags <s> and </s>.The program reads in a word sequence, finds the most likely locations of segment boundaries according to the language model, and outputs the word sequence with segment boundaries marked by <s> tags.<H2> OPTIONS </H2><P>Each filename argument can be an ASCII file, or a compressed file (name ending in .Z or .gz), or ``-'' to indicatestdin/stdout.<DL><DT><B> -help </B><DD>Print option summary.<DT><B> -version </B><DD>Print version information.<DT><B>-order</B><I> n</I><B></B><DD>Set the maximal N-gram order to be used, by default 3.NOTE: The order of the model is not set automatically when a modelfile is read, so the same file can be used at various orders.<DT><B>-debug</B><I> level</I><B></B><DD>Set the debugging output level (0 means no debugging output).Debugging messages are sent to stderr.<DT><B>-lm</B><I> file</I><B></B><DD>Read the N-gram model from<I>file</I>.<I></I><DT><B>-text</B><I> file</I><B></B><DD>Find the text to be segmented in <I>file</I>.<I></I>Default input is stdin.<DT><B> -continuous </B><DD>Process all words in the input as one sequence of words, irrespective ofline breaks.Normally each line is processed separately as a word sequence.<DT><B> -posteriors </B><DD>Use a forward-backward algorithm to compute the posterior probabilitiesof a segment boundary at each word transition, and hypothesize a boundarywhenever the probability exceeds 0.5.By default a Viterbi algorithm is used that computesthe globally most likely segmentation.<BR>If<B> -continuous </B>is specified as well,then this option will produce one line of output per word, containing,respectively, the <s> tag (if appropriate), the word itself, and the posterior probability for a boundary preceding the word.<DT><B> -unk </B><DD>Output the unknown word token <unk> for each input word not in the language model vocabulary.The default is to output the input word unchanged.<DT><B>-stag</B><I> string</I><B></B><DD>Use<I> string </I>to mark segment boundaries in the output.Default is the start-of-sentence symbol defined in the language model (<s>).<DT><B>-bias</B><I> b</I><B></B><DD>Make a segment boundary a priori more likely by a factor of<I>b</I>.<I></I>This allows balancing of false detection/rejection errors.The default is 1.</DD></DL><H2> SEE ALSO </H2><A HREF="ngram-count.html">ngram-count(1)</A>, <A HREF="ngram-format.html">ngram-format(5)</A>.<BR>A. Stolcke and E. Shriberg, ``Automatic Linguistic Segmentation ofSpontaneous Speech,'' <I>Proc. ICSLP</I>, 1005-1008, 1996.<H2> BUGS </H2>Only N-grams models up to trigram order are used accurately.For higher-order models use the more general <A HREF="hidden-ngram.html">hidden-ngram(1)</A>.<H2> AUTHOR </H2>Andreas Stolcke <stolcke@speech.sri.com>.<BR>Copyright 1997-2004 SRI International</BODY></HTML>⌨️ 快捷键说明
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