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ngram_test_main.cc
/*************************************************************************/
/* */
/* Centre for Speech Technology Research */
/* University of Edinburgh, UK */
/* Copyright (c) 1995,1996 */
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/* */
/*************************************************************************/
/* Authors: Simon King */
/* Date : July 1995 */
/*-----------------------------------------------------------------------*/
/* EST_Ngrammar test program */
/* */
/*=======================================================================*/
#include "EST.h"
#include "EST_Ngrammar.h"
/** @name <command>ngram_test</command> <emphasis> Test n-gram language model </emphasis>
@id ngram_test_manual
* @toc
*/
//@{
/**@name Synopsis
*/
//@{
//@synopsis
/**
ngram_test is for testing ngram models generated from
<link linkend=ngram-build-manual>ngram_build</link>.
<formalpara> <para> <title> How do we test an ngram model ? </title>
</para>
<para> ngram_test will compute the entropy (or perplexity, see below)
of some test data, given an ngram model. The entropy gives a measure
of how likely the ngram model is to have generated the test
data. Entropy is defined (for a sliding-window type ngram) as:
\‍[H = -\frac{1}{Q} \sum_{i=1}^{Q} log P(w_i | w_{i-1}, w_{i-2},... w_{i-N+1}) \‍]
where \‍(Q\‍) is the number of words of test data and \‍(N\‍) is the order
of the ngram model. Perplexity is a more intuitive mease, defined as:
\‍[B = 2^H \‍]
The perplexity of an ngram model with vocabulary size V will be
between 1 and V. Low perplexity indicates a more predictable language,
and in speech recognition, a models with low perplexity on test data
(i.e. data NOT used to estimate the model in the first place)
typically give better accuracy recognition than models with higher
perplexity (this is not guaranteed, however).
test_ngram works with non-sliding-window type models when the input
format is <parameter>ngram_per_line</parameter>.
</para>
</formalpara>
<formalpara>
<para><title>Input data format</title></para>
<para> The data input format options are the same as
<link linkend=ngram-build-manual>ngram_build</link>, as is the treatment of sentence start/end using
special tags.
</para>
<para>
Note: To get meaningful entropy/perplexity figures, it is recommended that
you use the same data input format in both
<link linkend=ngram-build-manual>ngram_build</link> and <link linkend=ngram-test-manual>ngram_test</link>, and the treatment of
sentence start/end should be the same.
</para>
</formalpara>
@see ngram_build */
//@}
/**@name OPTIONS
*/
//@{
//@options
//@}
int main(int argc, char **argv)
{
//int order;
EST_StrList files,script;
EST_Option al, op;
EST_String wordlist_file, script_file, in_file, format;
EST_String prev_tag, prev_prev_tag, last_tag;
EST_Litem *p;
//EST_Ngrammar::representation_t representation =
//EST_Ngrammar::dense;
EST_StrList wordlist;
EST_Ngrammar ngrammar;
bool per_file_stats=false;
bool raw_stats=false;
bool brief=false;
EST_String input_format;
double raw_entropy,count,entropy,perplexity,total_raw_H,total_count;
total_count = 0;
total_raw_H = 0;
parse_command_line
(argc, argv,
EST_String("[input file0] [input file1] ...\n")+
"-g <ifile> grammar file (required)\n"+
"-w <ifile> filename containing word list (required for some grammar formats)\n"+
"-S <ifile> script file\n"+
"-raw_stats print unnormalised entropy and sample count\n"+
"-brief print results in brief format\n"+
"-f print stats for each file\n"+
"\n"+
"-input_format <string>\n"+
" format of input data (default sentence_per_line)\n"+
" may also be sentence_per_file, or ngram_per_line.\n"+
"\n"+
"Pseudo-words :\n"+
"-prev_tag <string>\n"+
" tag before sentence start\n"+
"-prev_prev_tag <string>\n"+
" all words before 'prev_tag'\n"+
"-last_tag <string>\n"+
" after sentence end\n"+
"-default_tags\n"+
" use default tags of "+SENTENCE_START_MARKER+
","+SENTENCE_END_MARKER+" and "+SENTENCE_END_MARKER+"\n"+
" respectively\n",
files, al);
if (al.present("-w"))
wordlist_file = al.val("-w");
else{
wordlist_file = "";
}
if (al.present("-f"))
per_file_stats = true;
if (al.present("-input_format"))
input_format = al.val("-input_format");
else
input_format = "sentence_per_line";
if ( al.present("-raw_stats") || al.present("-r"))
raw_stats = true;
if ( al.present("-brief") || al.present("-b") )
brief = true;
if (al.present("-default_tags"))
{
prev_tag = SENTENCE_START_MARKER;
prev_prev_tag = SENTENCE_END_MARKER;
last_tag = SENTENCE_END_MARKER;
}
if (al.present("-prev_tag"))
{
if (al.present("-default_tags"))
cerr << "test_ngram: WARNING : -prev_tag overrides -default_tags"
<< endl;
prev_tag = al.val("-prev_tag");
}
if (al.present("-prev_prev_tag"))
{
if (al.present("-default_tags"))
cerr << "test_ngram: WARNING : -prev_prev_tag overrides -default_tags" << endl;
prev_prev_tag = al.val("-prev_prev_tag");
}
if (al.present("-last_tag"))
{
if (al.present("-default_tags"))
cerr << "test_ngram: WARNING : -last_tag overrides -default_tags" << endl;
last_tag = al.val("-last_tag");
}
if ( ( (prev_tag=="") || (prev_prev_tag=="") || (last_tag=="") )
&& ( (prev_tag!="") || (prev_prev_tag!="") || (last_tag!="") ) )
{
cerr << "test_ngram: ERROR : if any tags are given, ALL must be given" << endl;
exit(1);
}
// script
if (al.present("-S"))
{
script_file = al.val("-S");
if(load_StrList(script_file,script) != format_ok)
{
cerr << "test_ngram: Could not read script from file "
<< script_file << endl;
exit(1);
}
}
if (al.present("-g"))
in_file = al.val("-g");
else
{
cerr << "test_ngram: Must give a grammar filename using -g" << endl;
exit(1);
}
// plus any files on command line
// except file "-" unless there is no script
if(script.head()==NULL)
script += files;
else
for(p=files.head();p!=0;p=p->next())
if(files(p) != "-")
script.append(files(p));
if(script.head() == NULL)
{
cerr << "test_ngram: No test files given" << endl;
exit(1);
}
if (wordlist_file != "")
{
// load wordlist
if (load_StrList(wordlist_file,wordlist) != format_ok)
{
cerr << "test_ngram: Could not read wordlist from file " << wordlist_file
<< endl;
exit(1);
}
// load grammar using wordlist
if (ngrammar.load(in_file,wordlist) != format_ok)
{
cerr << "test_ngram: Failed to load grammar" << endl;
exit(1);
}
}
else
{
if (ngrammar.load(in_file) != format_ok)
{
cerr << "test_ngram: Failed to load grammar" << endl;
exit(1);
}
}
if (!brief)
{
cout << "Ngram Test Results" << endl;
cout << "==================" << endl;
}
for (p = script.head(); p; p = p->next())
{
// test each file
if (test_stats(ngrammar,
script(p),
raw_entropy,count,
entropy,perplexity,
input_format,
prev_tag,
prev_prev_tag))
{
total_raw_H += raw_entropy;
total_count += count;
if(per_file_stats)
{
if (brief)
cout << basename(script(p)) << " \t";
else
cout << script(p) << endl;
if(raw_stats)
{
if (brief)
cout << raw_entropy << " " << count << " ";
else
{
cout << " raw entropy " << raw_entropy << endl;
cout << " count " << count << endl;
}
}
if (brief)
cout << entropy << " " << perplexity << endl;
else
{
cout << " entropy " << entropy << endl;
cout << " perplexity " << perplexity << endl << endl;
}
}
}
else
{
cerr << "test_ngram: WARNING : file '" << script(p)
<< "' could not be processed" << endl;
}
}
if (total_count > 0)
{
if (!brief)
cout << "Summary for grammar " << in_file << endl;
else
if (per_file_stats)
cout << "summary \t";
if(raw_stats)
{
if (brief)
cout << total_raw_H << " " << total_count << " ";
else
{
cout << " raw entropy " << total_raw_H << endl;
cout << " count " << total_count << endl;
}
}
if (brief)
{
cout << total_raw_H / total_count;
cout << " " << pow(2.0,total_raw_H / total_count);
cout << endl;
}
else
{
cout << " entropy " << total_raw_H / total_count << endl;
cout << " perplexity " << pow(2.0,total_raw_H / total_count);
cout << endl;
}
}
else
{
cerr << "test_ngram: No data processed" << endl;
}
// everything went okay
return 0;
}
void override_lib_ops(EST_Option &a_list, EST_Option &al)
{
(void)a_list;
(void)al;
}
/** @name Hints
<title>I got a perplexity of Infinity - what went wrong ?</title>
A perplexity of Infinity means that at least one of the ngrams in your
test data had a probability of zero. Possible reasons for this include:
<itemizedlist>
<listitem><para>The training data had no examples of this ngram, and
you did not specify a floor for zero frequency ngrams in
\Ref{build_ngram} </para></listitem>
<listitem><para>You used differing input formats for \Ref{ngram_build}
and \Ref{ngram_test}. </para></listitem>
<listitem><para>You used differing sentence start/end treatments in
\Ref{ngram_build} and \Ref{ngram_test}. </para></listitem>
</itemizedlist>
*/
//@{
//@}
//@}
EST_Ngrammar
Definition EST_Ngrammar.h:209
EST_Option
Definition EST_Option.h:50
EST_String
Definition EST_String.h:70
EST_TKVL::val
const V & val(const K &rkey, bool m=0) const
return value according to key (const)
Definition EST_TKVL.cc:145
EST_TKVL::present
const int present(const K &rkey) const
Returns true if key is present.
Definition EST_TKVL.cc:222
EST_TList::append
void append(const T &item)
add item onto end of list
Definition EST_TList.h:191