mirror of
https://github.com/moses-smt/mosesdecoder.git
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a25193cc5d
This is lint reported by the new lint-checking functionality in beautify.py. (We can change to a different lint checker if we have a better one, but it would probably still flag these same problems.) Lint checking can help a lot, but only if we get the lint under control.
1169 lines
41 KiB
Prolog
Executable File
1169 lines
41 KiB
Prolog
Executable File
#!/usr/bin/env perl
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use warnings;
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use strict;
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use utf8;
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use Encode;
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use XML::Twig;
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binmode STDOUT, ":utf8";
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binmode STDERR, ":utf8";
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#################################
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# History:
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#
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# version 13a
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# * modified the scoring functions to prevent division-by-zero errors when a system segment is empty
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# * affected methods: 'bleu_score' and 'bleu_score_smoothing'
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#
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# version 13
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# * Uses a XML parser to read data (only when extension is .xml)
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# * Smoothing of the segment-level BLEU scores, done by default
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# * smoothing method similar to that of bleu-1.04.pl (IBM)
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# * see comments above the 'bleu_score' method for more details on how the smoothing is computed
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# * added a '--no-smoothing' option to simulate old scripts behavior
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# * Introduction of the 'brevity-penalty' option, taking one of two values:
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# * 'closest' (default) : act as IBM BLEU (taking the closest reference translation length)
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# * in case two reference translations are at the same distance, will take the shortest one
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# * for more details regarding how the BP is computed, see comments of the 'brevity_penalty_closest' function
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# * 'shortest' : act as previous versions of the script (taking shortest reference translation length)
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# * Introduction of the 'international-tokenization' option, boolean, disabled by default
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# by default (when the option is not provided), uses 11b's tokenization function
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# when option specified, uses v12's tokenization function
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# * Introduction of a 'Metrics MATR output' flag (option '--metricsMATR')
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# when used, creates three files for both BLEU score and NIST score:
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# * BLEU-seg.scr and NIST-seg.scr: contain segment-level scores
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# * BLEU-doc.scr and NIST-doc.scr: contain document-level scores
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# * BLEU-sys.scr and NIST-sys.scr: contain system-level scores
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# * SGML parsing
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# * script will halt if source, reference and test files don't share the same setid attribute value (used for metricsMATR output)
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# * correct segment IDs extracted from the files (was previously using an array, and using the index as a segID for output)
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# * detailed output flag (-d) can now be used when running both BLEU and NIST
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#
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# version 12
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# * Text normalization changes:
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# * convert entity references (only the entities declared in the DTD)
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# * now uses unicode categories
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# * tokenize punctuation unless followed AND preceded by digits
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# * tokenize symbols
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# * UTF-8 handling:
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# * files are now read using utf8 mode
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# * Added the '-e' command-line option to enclose non-ASCII characters between spaces
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#
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# version 11b -- text normalization modified:
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# * take out the join digit line because it joins digits
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# when it shouldn't have
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# $norm_text =~ s/(\d)\s+(?=\d)/$1/g; #join digits
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#
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# version 11a -- corrected output of individual n-gram precision values
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#
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# version 11 -- bug fixes:
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# * make filehandle operate in binary mode to prevent Perl from operating
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# (by default in Red Hat 9) in UTF-8
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# * fix failure on joining digits
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# version 10 -- updated output to include more details of n-gram scoring.
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# Defaults to generate both NIST and BLEU scores. Use -b for BLEU
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# only, use -n for NIST only
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#
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# version 09d -- bug fix (for BLEU scoring, ngrams were fixed at 4
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# being the max, regardless what was entered on the command line.)
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#
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# version 09c -- bug fix (During the calculation of ngram information,
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# each ngram was being counted only once for each segment. This has
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# been fixed so that each ngram is counted correctly in each segment.)
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#
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# version 09b -- text normalization modified:
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# * option flag added to preserve upper case
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# * non-ASCII characters left in place.
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#
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# version 09a -- text normalization modified:
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# * " and & converted to "" and &, respectively
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# * non-ASCII characters kept together (bug fix)
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#
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# version 09 -- modified to accommodate sgml tag and attribute
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# names revised to conform to default SGML conventions.
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#
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# version 08 -- modifies the NIST metric in accordance with the
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# findings on the 2001 Chinese-English dry run corpus. Also
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# incorporates the BLEU metric as an option and supports the
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# output of ngram detail.
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#
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# version 07 -- in response to the MT meeting on 28 Jan 2002 at ISI
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# Keep strings of non-ASCII characters together as one word
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# (rather than splitting them into one-character words).
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# Change length penalty so that translations that are longer than
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# the average reference translation are not penalized.
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#
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# version 06
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# Prevent divide-by-zero when a segment has no evaluation N-grams.
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# Correct segment index for level 3 debug output.
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#
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# version 05
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# improve diagnostic error messages
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#
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# version 04
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# tag segments
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#
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# version 03
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# add detailed output option (intermediate document and segment scores)
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#
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# version 02
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# accommodation of modified sgml tags and attributes
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#
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# version 01
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# same as bleu version 15, but modified to provide formal score output.
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#
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# original IBM version
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# Author: Kishore Papineni
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# Date: 06/10/2001
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#################################
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######
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# Intro
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my ($date, $time) = date_time_stamp();
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print "MT evaluation scorer began on $date at $time\n";
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print "command line: ", $0, " ", join(" ", @ARGV), "\n";
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my $usage = "\n\nUsage: $0 -r <ref_file> -s <src_file> -t <tst_file>\n\n".
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"Description: This Perl script evaluates MT system performance.\n".
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"\n".
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"Required arguments:\n".
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" -r <ref_file> is a file containing the reference translations for\n".
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" the documents to be evaluated.\n".
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" -s <src_file> is a file containing the source documents for which\n".
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" translations are to be evaluated\n".
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" -t <tst_file> is a file containing the translations to be evaluated\n".
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"\n".
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"Optional arguments:\n".
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" -h prints this help message to STDOUT\n".
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" -c preserves upper-case alphabetic characters\n".
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" -b generate BLEU scores only\n".
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" -n generate NIST scores only\n".
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" -d detailed output flag:\n".
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" 0 (default) for system-level score only\n".
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" 1 to include document-level scores\n".
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" 2 to include segment-level scores\n".
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" 3 to include ngram-level scores\n".
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" -e enclose non-ASCII characters between spaces\n".
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" --brevity-penalty ( closest | shortest )\n" .
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" closest (default) : acts as IBM BLEU (takes the closest reference translation length)\n" .
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" shortest : acts as previous versions of the script (takes the shortest reference translation length)\n" .
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" --international-tokenization\n" .
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" when specified, uses Unicode-based (only) tokenization rules\n" .
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" when not specified (default), uses default tokenization (some language-dependant rules)\n" .
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" --metricsMATR : create three files for both BLEU scores and NIST scores:\n" .
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" BLEU-seg.scr and NIST-seg.scr : segment-level scores\n" .
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" BLEU-doc.scr and NIST-doc.scr : document-level scores\n" .
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" BLEU-sys.scr and NIST-sys.scr : system-level scores\n" .
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" --no-smoothing : disable smoothing on BLEU scores\n" .
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"\n";
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use vars qw ($opt_r $opt_s $opt_t $opt_d $opt_h $opt_b $opt_n $opt_c $opt_x $opt_e);
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use Getopt::Long;
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my $ref_file = '';
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my $src_file = '';
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my $tst_file = '';
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my $detail = 0;
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my $help = '';
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my $preserve_case = '';
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my $split_non_ASCII = '';
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my $brevity_penalty = 'closest';
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my $international_tokenization;
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my $metricsMATR_output = '';
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my $no_smoothing = '';
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our $opt_x = '';
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our $opt_b = '';
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our $opt_n = '';
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GetOptions(
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'r=s' => \$ref_file,
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's=s' => \$src_file,
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't=s' => \$tst_file,
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'd:i' => \$detail,
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'h|help' => \$help,
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'b',
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'n',
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'c' => \$preserve_case,
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'x:s',
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'e' => \$split_non_ASCII,
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'brevity-penalty:s' => \$brevity_penalty,
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'international-tokenization' => \$international_tokenization,
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'metricsMATR-output' => \$metricsMATR_output,
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'no-smoothing' => \$no_smoothing
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);
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die $usage if $help;
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die "Error in command line: ref_file not defined$usage" unless ( $ref_file );
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die "Error in command line: src_file not defined$usage" unless ( $src_file );
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die "Error in command line: tst_file not defined$usage" unless ( $tst_file );
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my $BLEU_BP;
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if ( !( $brevity_penalty cmp 'closest' ) )
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{
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$BLEU_BP = \&brevity_penalty_closest;
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}
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elsif ( !( $brevity_penalty cmp 'shortest' ) )
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{
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$BLEU_BP = \&brevity_penalty_shortest;
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}
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else
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{
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die "Incorrect value supplied for 'brevity_penalty'$usage";
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}
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my $TOKENIZATION = \&tokenization;
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$TOKENIZATION = \&tokenization_international if ( $international_tokenization );
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my $BLEU_SCORE = \&bleu_score;
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$BLEU_SCORE = \&bleu_score_nosmoothing if ( $no_smoothing );
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my $max_Ngram = 9;
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my $METHOD = "BOTH";
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if ( $opt_b ) { $METHOD = "BLEU"; }
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if ( $opt_n ) { $METHOD = "NIST"; }
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my $method;
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######
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# Global variables
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my ($src_lang, $tgt_lang, @tst_sys, @ref_sys); # evaluation parameters
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my (%tst_data, %ref_data); # the data -- with structure: {system}{document}{segments}
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my ($src_id, $ref_id, $tst_id); # unique identifiers for ref and tst translation sets
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my %eval_docs; # document information for the evaluation data set
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my %ngram_info; # the information obtained from (the last word in) the ngram
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######
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# Get source document ID's
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($src_id) = get_source_info ($src_file);
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######
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# Get reference translations
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($ref_id) = get_MT_data (\%ref_data, "RefSet", $ref_file);
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compute_ngram_info ();
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######
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# Get translations to evaluate
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($tst_id) = get_MT_data (\%tst_data, "TstSet", $tst_file);
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######
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# Check data for completeness and correctness
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check_MT_data ();
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######
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#
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my %NISTmt;
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my %NISTOverall;
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my %BLEUmt;
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my %BLEUOverall;
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######
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# Evaluate
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print " Evaluation of $src_lang-to-$tgt_lang translation using:\n";
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my $cum_seg = 0;
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foreach my $doc (sort keys %eval_docs)
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{
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$cum_seg += scalar( keys( %{$eval_docs{$doc}{SEGS}} ) );
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}
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print " src set \"$src_id\" (", scalar keys %eval_docs, " docs, $cum_seg segs)\n";
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print " ref set \"$ref_id\" (", scalar keys %ref_data, " refs)\n";
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print " tst set \"$tst_id\" (", scalar keys %tst_data, " systems)\n\n";
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foreach my $sys (sort @tst_sys)
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{
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for (my $n=1; $n<=$max_Ngram; $n++)
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{
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$NISTmt{$n}{$sys}{cum} = 0;
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$NISTmt{$n}{$sys}{ind} = 0;
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$BLEUmt{$n}{$sys}{cum} = 0;
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$BLEUmt{$n}{$sys}{ind} = 0;
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}
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if ( ($METHOD eq "BOTH") || ($METHOD eq "NIST") )
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{
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$method="NIST";
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score_system ($sys, \%NISTmt, \%NISTOverall);
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}
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if ( ($METHOD eq "BOTH") || ($METHOD eq "BLEU") )
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{
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$method="BLEU";
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score_system ($sys, \%BLEUmt, \%BLEUOverall);
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}
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}
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######
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printout_report ();
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if ( $metricsMATR_output )
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{
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outputMetricsMATR( 'NIST', %NISTOverall ) if ( ( $METHOD eq 'BOTH' ) || ( $METHOD eq 'NIST' ) );
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outputMetricsMATR( 'BLEU', %BLEUOverall ) if ( ( $METHOD eq 'BOTH' ) || ( $METHOD eq 'BLEU' ) );
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}
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($date, $time) = date_time_stamp();
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print "MT evaluation scorer ended on $date at $time\n";
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exit 0;
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#################################
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sub get_source_info
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{
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my ($file) = @_;
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my ($name, $id, $src, $doc, $seg);
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my ($data, $tag, $span);
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# Extension of the file determines the parser used:
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# .xml : XML::Twig
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# otherwise : simple SGML parsing functions
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if ( $file =~ /\.xml$/i )
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{
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my $twig = XML::Twig->new();
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$twig->parsefile( $file );
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my $root = $twig->root;
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my $currentSet = $root->first_child( 'srcset' );
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die "Source XML file '$file' does not contain the 'srcset' element" if ( not $currentSet );
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$id = $currentSet->{ 'att' }->{ 'setid' } or die "No 'setid' attribute value in '$file'";
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$src = $currentSet->{ 'att' }->{ 'srclang' } or die "No srcset 'srclang' attribute value in '$file'";
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die "Not the same srclang attribute values across sets" unless ( not defined $src_lang or $src eq $src_lang );
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$src_lang = $src;
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foreach my $currentDoc ( $currentSet->get_xpath( './/doc' ) )
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{
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my $docID = $currentDoc->{ 'att' }->{ 'docid' } or die "No document 'docid' attribute value in '$file'";
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foreach my $currentSeg ( $currentDoc->get_xpath( './/seg' ) )
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{
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my $segID = $currentSeg->{ 'att' }->{ 'id' } or die "No segment 'id' attribute value in '$file'";
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my $segData = $currentSeg->text;
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($eval_docs{$docID}{SEGS}{$segID}) = &{ $TOKENIZATION }( $segData );
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}
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}
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}
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else
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{
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#read data from file
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open (FILE, $file) or die "\nUnable to open translation data file '$file'", $usage;
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binmode FILE, ":utf8";
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$data .= $_ while <FILE>;
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close (FILE);
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#get source set info
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die "\n\nFATAL INPUT ERROR: no 'src_set' tag in src_file '$file'\n\n"
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unless ($tag, $span, $data) = extract_sgml_tag_and_span ("SrcSet", $data);
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die "\n\nFATAL INPUT ERROR: no tag attribute '$name' in file '$file'\n\n"
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unless ($id) = extract_sgml_tag_attribute ($name="SetID", $tag);
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die "\n\nFATAL INPUT ERROR: no tag attribute '$name' in file '$file'\n\n"
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unless ($src) = extract_sgml_tag_attribute ($name="SrcLang", $tag);
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die "\n\nFATAL INPUT ERROR: $name ('$src') in file '$file' inconsistent\n"
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." with $name in previous input data ('$src_lang')\n\n"
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unless (not defined $src_lang or $src eq $src_lang);
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$src_lang = $src;
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#get doc info -- ID and # of segs
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$data = $span;
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while (($tag, $span, $data) = extract_sgml_tag_and_span ("Doc", $data))
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{
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die "\n\nFATAL INPUT ERROR: no tag attribute '$name' in file '$file'\n\n"
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unless ($doc) = extract_sgml_tag_attribute ($name="DocID", $tag);
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die "\n\nFATAL INPUT ERROR: duplicate '$name' in file '$file'\n\n"
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if defined $eval_docs{$doc};
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$span =~ s/[\s\n\r]+/ /g; # concatenate records
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my $nseg=0, my $seg_data = $span;
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while (($tag, $span, $seg_data) = extract_sgml_tag_and_span ("Seg", $seg_data))
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{
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die "\n\nFATAL INPUT ERROR: no attribute '$name' in file '$file'\n\n"
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unless ($seg) = extract_sgml_tag_attribute( $name='id', $tag );
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($eval_docs{$doc}{SEGS}{$seg}) = &{ $TOKENIZATION }( $span );
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$nseg++;
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}
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die "\n\nFATAL INPUT ERROR: no segments in document '$doc' in file '$file'\n\n"
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if $nseg == 0;
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}
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die "\n\nFATAL INPUT ERROR: no documents in file '$file'\n\n"
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unless keys %eval_docs > 0;
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}
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return $id;
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}
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#################################
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sub get_MT_data
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{
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my ($docs, $set_tag, $file) = @_;
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my ($name, $id, $src, $tgt, $sys, $doc, $seg);
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my ($tag, $span, $data);
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# Extension of the file determines the parser used:
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# .xml : XML::Twig
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# otherwise : simple SGML parsing functions
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if ( $file =~ /\.xml$/i )
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{
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my $twig = XML::Twig->new();
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$twig->parsefile( $file );
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my $root = $twig->root;
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foreach my $currentSet ( $root->get_xpath( 'refset' ), $root->get_xpath( 'tstset' ) )
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{
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$id = $currentSet->{ 'att' }->{ 'setid' } or die "No 'setid' attribute value in '$file'";
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$src = $currentSet->{ 'att' }->{ 'srclang' } or die "No 'srclang' attribute value in '$file'";
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$tgt = $currentSet->{ 'att' }->{ 'trglang' } or die "No 'trglang' attribute value in '$file'";
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die "Not the same 'srclang' attribute value across sets" unless ( $src eq $src_lang );
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die "Not the same 'trglang' attribute value across sets" unless ( ( not defined $tgt_lang ) or ( $tgt = $tgt_lang ) );
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$tgt_lang = $tgt;
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my $sys;
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if ( $currentSet->name eq 'tstset' )
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{
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$sys = $currentSet->{ 'att' }->{ 'sysid' } or die "No 'sysid' attribute value in '$file'";
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}
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else
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{
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$sys = $currentSet->{ 'att' }->{ 'refid' } or die "No 'refid' attribute value in '$file'";
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}
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foreach my $currentDoc ( $currentSet->get_xpath( './/doc' ) )
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{
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my $docID = $currentDoc->{ 'att' }->{ 'docid' } or die "No document 'docid' attribute value in '$file'";
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$docs->{ $sys }{ $docID }{ FILE } = $file;
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foreach my $currentSeg ( $currentDoc->get_xpath( './/seg' ) )
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{
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my $segID = $currentSeg->{ 'att' }->{ 'id' } or die "No segment 'id' attribute value in '$file'";
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my $segData = $currentSeg->text;
|
|
($docs->{$sys}{$docID}{SEGS}{$segID}) = &{ $TOKENIZATION }( $segData );
|
|
}
|
|
}
|
|
}
|
|
}
|
|
else
|
|
{
|
|
#read data from file
|
|
open (FILE, $file) or die "\nUnable to open translation data file '$file'", $usage;
|
|
binmode FILE, ":utf8";
|
|
$data .= $_ while <FILE>;
|
|
close (FILE);
|
|
|
|
#get tag info
|
|
while (($tag, $span, $data) = extract_sgml_tag_and_span ($set_tag, $data))
|
|
{
|
|
die "\n\nFATAL INPUT ERROR: no tag attribute '$name' in file '$file'\n\n"
|
|
unless ($id) = extract_sgml_tag_attribute ($name="SetID", $tag);
|
|
die "\n\nFATAL INPUT ERROR: no tag attribute '$name' in file '$file'\n\n"
|
|
unless ($src) = extract_sgml_tag_attribute ($name="SrcLang", $tag);
|
|
die "\n\nFATAL INPUT ERROR: $name ('$src') in file '$file' inconsistent\n"
|
|
." with $name of source ('$src_lang')\n\n"
|
|
unless $src eq $src_lang;
|
|
die "\n\nFATAL INPUT ERROR: no tag attribute '$name' in file '$file'\n\n"
|
|
unless ($tgt) = extract_sgml_tag_attribute ($name="TrgLang", $tag);
|
|
die "\n\nFATAL INPUT ERROR: $name ('$tgt') in file '$file' inconsistent\n"
|
|
." with $name of the evaluation ('$tgt_lang')\n\n"
|
|
unless (not defined $tgt_lang or $tgt eq $tgt_lang);
|
|
$tgt_lang = $tgt;
|
|
|
|
my $mtdata = $span;
|
|
while (($tag, $span, $mtdata) = extract_sgml_tag_and_span ("Doc", $mtdata))
|
|
{
|
|
die "\n\nFATAL INPUT ERROR: no tag attribute '$name' in file '$file'\n\n"
|
|
unless (my $sys) = extract_sgml_tag_attribute ($name="SysID", $tag);
|
|
die "\n\nFATAL INPUT ERROR: no tag attribute '$name' in file '$file'\n\n"
|
|
unless $doc = extract_sgml_tag_attribute ($name="DocID", $tag);
|
|
die "\n\nFATAL INPUT ERROR: document '$doc' for system '$sys' in file '$file'\n"
|
|
." previously loaded from file '$docs->{$sys}{$doc}{FILE}'\n\n"
|
|
unless (not defined $docs->{$sys}{$doc});
|
|
|
|
$span =~ s/[\s\n\r]+/ /g; # concatenate records
|
|
my $nseg=0, my $seg_data = $span;
|
|
while (($tag, $span, $seg_data) = extract_sgml_tag_and_span ("Seg", $seg_data))
|
|
{
|
|
die "\n\nFATAIL INPUT ERROR: no tag attribute '$name' in file '$file'\n\n"
|
|
unless $seg = extract_sgml_tag_attribute( $name="id", $tag );
|
|
($docs->{$sys}{$doc}{SEGS}{$seg}) = &{ $TOKENIZATION }( $span );
|
|
$nseg++;
|
|
}
|
|
die "\n\nFATAL INPUT ERROR: no segments in document '$doc' in file '$file'\n\n" if $nseg == 0;
|
|
$docs->{$sys}{$doc}{FILE} = $file;
|
|
}
|
|
}
|
|
}
|
|
return $id;
|
|
}
|
|
|
|
#################################
|
|
|
|
sub check_MT_data
|
|
{
|
|
@tst_sys = sort keys %tst_data;
|
|
@ref_sys = sort keys %ref_data;
|
|
|
|
die "Not the same 'setid' attribute values across files" unless ( ( $src_id eq $tst_id ) && ( $src_id eq $ref_id ) );
|
|
|
|
#every evaluation document must be represented for every system and every reference
|
|
foreach my $doc (sort keys %eval_docs)
|
|
{
|
|
my $nseg_source = scalar( keys( %{$eval_docs{$doc}{SEGS}} ) );
|
|
foreach my $sys (@tst_sys)
|
|
{
|
|
die "\n\nFATAL ERROR: no document '$doc' for system '$sys'\n\n" unless defined $tst_data{$sys}{$doc};
|
|
my $nseg = scalar( keys( %{$tst_data{$sys}{$doc}{SEGS}} ) );
|
|
die "\n\nFATAL ERROR: translated documents must contain the same # of segments as the source, but\n"
|
|
." document '$doc' for system '$sys' contains $nseg segments, while\n"
|
|
." the source document contains $nseg_source segments.\n\n"
|
|
unless $nseg == $nseg_source;
|
|
}
|
|
foreach my $sys (@ref_sys)
|
|
{
|
|
die "\n\nFATAL ERROR: no document '$doc' for reference '$sys'\n\n" unless defined $ref_data{$sys}{$doc};
|
|
my $nseg = scalar( keys( %{$ref_data{$sys}{$doc}{SEGS}} ) );
|
|
die "\n\nFATAL ERROR: translated documents must contain the same # of segments as the source, but\n"
|
|
." document '$doc' for system '$sys' contains $nseg segments, while\n"
|
|
." the source document contains $nseg_source segments.\n\n"
|
|
unless $nseg == $nseg_source;
|
|
}
|
|
}
|
|
}
|
|
|
|
#################################
|
|
|
|
sub compute_ngram_info
|
|
{
|
|
my ($ref, $doc, $seg);
|
|
my (@wrds, $tot_wrds, %ngrams, $ngram, $mgram);
|
|
my (%ngram_count, @tot_ngrams);
|
|
|
|
foreach $ref (keys %ref_data)
|
|
{
|
|
foreach $doc (keys %{$ref_data{$ref}})
|
|
{
|
|
foreach $seg ( keys %{$ref_data{$ref}{$doc}{SEGS}})
|
|
{
|
|
@wrds = split /\s+/, $ref_data{ $ref }{ $doc }{ SEGS }{ $seg };
|
|
$tot_wrds += @wrds;
|
|
%ngrams = %{Words2Ngrams (@wrds)};
|
|
foreach $ngram (keys %ngrams)
|
|
{
|
|
$ngram_count{$ngram} += $ngrams{$ngram};
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
foreach $ngram (keys %ngram_count)
|
|
{
|
|
@wrds = split / /, $ngram;
|
|
pop @wrds, $mgram = join " ", @wrds;
|
|
$ngram_info{$ngram} = - log ($mgram ? $ngram_count{$ngram}/$ngram_count{$mgram} : $ngram_count{$ngram}/$tot_wrds) / log 2;
|
|
if (defined $opt_x and $opt_x eq "ngram info")
|
|
{
|
|
@wrds = split / /, $ngram;
|
|
printf "ngram info:%9.4f%6d%6d%8d%3d %s\n", $ngram_info{$ngram}, $ngram_count{$ngram},
|
|
$mgram ? $ngram_count{$mgram} : $tot_wrds, $tot_wrds, scalar @wrds, $ngram;
|
|
}
|
|
}
|
|
}
|
|
|
|
#################################
|
|
|
|
sub score_system
|
|
{
|
|
my ($sys, $ref, $doc, $SCOREmt, $overallScore);
|
|
($sys, $SCOREmt, $overallScore) = @_;
|
|
my ($ref_length, $match_cnt, $tst_cnt, $ref_cnt, $tst_info, $ref_info);
|
|
my ($cum_ref_length, @cum_match, @cum_tst_cnt, @cum_ref_cnt, @cum_tst_info, @cum_ref_info);
|
|
|
|
$cum_ref_length = 0;
|
|
for (my $j=1; $j<=$max_Ngram; $j++)
|
|
{
|
|
$cum_match[$j] = $cum_tst_cnt[$j] = $cum_ref_cnt[$j] = $cum_tst_info[$j] = $cum_ref_info[$j] = 0;
|
|
}
|
|
foreach $doc (sort keys %eval_docs)
|
|
{
|
|
($ref_length, $match_cnt, $tst_cnt, $ref_cnt, $tst_info, $ref_info) = score_document ($sys, $doc, $overallScore);
|
|
if ( $method eq "NIST" )
|
|
{
|
|
my %DOCmt = ();
|
|
my $docScore = nist_score( scalar( @ref_sys ), $match_cnt, $tst_cnt, $ref_cnt, $tst_info, $ref_info, $sys, \%DOCmt );
|
|
$overallScore->{ $sys }{ 'documents' }{ $doc }{ 'score' } = $docScore;
|
|
if ( $detail >= 1 )
|
|
{
|
|
printf "$method score using 5-grams = %.4f for system \"$sys\" on document \"$doc\" (%d segments, %d words)\n",
|
|
$docScore, scalar keys %{$tst_data{$sys}{$doc}{SEGS}}, $tst_cnt->[1];
|
|
}
|
|
}
|
|
|
|
if ( $method eq "BLEU" )
|
|
{
|
|
my %DOCmt = ();
|
|
my $docScore = &{$BLEU_SCORE}( $ref_length, $match_cnt, $tst_cnt, $sys, \%DOCmt );
|
|
$overallScore->{ $sys }{ 'documents' }{ $doc }{ 'score' } = $docScore;
|
|
if ( $detail >= 1 )
|
|
{
|
|
printf "$method score using 4-grams = %.4f for system \"$sys\" on document \"$doc\" (%d segments, %d words)\n",
|
|
$docScore, scalar keys %{$tst_data{$sys}{$doc}{SEGS}}, $tst_cnt->[1];
|
|
}
|
|
}
|
|
|
|
$cum_ref_length += $ref_length;
|
|
for (my $j=1; $j<=$max_Ngram; $j++)
|
|
{
|
|
$cum_match[$j] += $match_cnt->[$j];
|
|
$cum_tst_cnt[$j] += $tst_cnt->[$j];
|
|
$cum_ref_cnt[$j] += $ref_cnt->[$j];
|
|
$cum_tst_info[$j] += $tst_info->[$j];
|
|
$cum_ref_info[$j] += $ref_info->[$j];
|
|
printf "document info: $sys $doc %d-gram %d %d %d %9.4f %9.4f\n", $j, $match_cnt->[$j],
|
|
$tst_cnt->[$j], $ref_cnt->[$j], $tst_info->[$j], $ref_info->[$j]
|
|
if (defined $opt_x and $opt_x eq "document info");
|
|
}
|
|
}
|
|
|
|
if ($method eq "BLEU")
|
|
{
|
|
$overallScore->{ $sys }{ 'score' } = &{$BLEU_SCORE}($cum_ref_length, \@cum_match, \@cum_tst_cnt, $sys, $SCOREmt, 1);
|
|
}
|
|
if ($method eq "NIST")
|
|
{
|
|
$overallScore->{ $sys }{ 'score' } = nist_score (scalar @ref_sys, \@cum_match, \@cum_tst_cnt, \@cum_ref_cnt, \@cum_tst_info, \@cum_ref_info, $sys, $SCOREmt);
|
|
}
|
|
}
|
|
|
|
#################################
|
|
|
|
sub score_document
|
|
{
|
|
my ($sys, $ref, $doc, $overallScore);
|
|
($sys, $doc, $overallScore) = @_;
|
|
my ($ref_length, $match_cnt, $tst_cnt, $ref_cnt, $tst_info, $ref_info);
|
|
my ($cum_ref_length, @cum_match, @cum_tst_cnt, @cum_ref_cnt, @cum_tst_info, @cum_ref_info);
|
|
|
|
$cum_ref_length = 0;
|
|
for (my $j=1; $j<=$max_Ngram; $j++)
|
|
{
|
|
$cum_match[$j] = $cum_tst_cnt[$j] = $cum_ref_cnt[$j] = $cum_tst_info[$j] = $cum_ref_info[$j] = 0;
|
|
}
|
|
|
|
#score each segment
|
|
foreach my $seg ( sort{ $a <=> $b } keys( %{$tst_data{$sys}{$doc}{SEGS}} ) )
|
|
{
|
|
my @ref_segments = ();
|
|
foreach $ref (@ref_sys)
|
|
{
|
|
push @ref_segments, $ref_data{$ref}{$doc}{SEGS}{$seg};
|
|
if ( $detail >= 3 )
|
|
{
|
|
printf "ref '$ref', seg $seg: %s\n", $ref_data{$ref}{$doc}{SEGS}{$seg}
|
|
}
|
|
|
|
}
|
|
|
|
printf "sys '$sys', seg $seg: %s\n", $tst_data{$sys}{$doc}{SEGS}{$seg} if ( $detail >= 3 );
|
|
($ref_length, $match_cnt, $tst_cnt, $ref_cnt, $tst_info, $ref_info) = score_segment ($tst_data{$sys}{$doc}{SEGS}{$seg}, @ref_segments);
|
|
|
|
if ( $method eq "BLEU" )
|
|
{
|
|
my %DOCmt = ();
|
|
my $segScore = &{$BLEU_SCORE}($ref_length, $match_cnt, $tst_cnt, $sys, %DOCmt);
|
|
$overallScore->{ $sys }{ 'documents' }{ $doc }{ 'segments' }{ $seg }{ 'score' } = $segScore;
|
|
if ( $detail >= 2 )
|
|
{
|
|
printf " $method score using 4-grams = %.4f for system \"$sys\" on segment $seg of document \"$doc\" (%d words)\n", $segScore, $tst_cnt->[1]
|
|
}
|
|
}
|
|
if ( $method eq "NIST" )
|
|
{
|
|
my %DOCmt = ();
|
|
my $segScore = nist_score (scalar @ref_sys, $match_cnt, $tst_cnt, $ref_cnt, $tst_info, $ref_info, $sys, %DOCmt);
|
|
$overallScore->{ $sys }{ 'documents' }{ $doc }{ 'segments' }{ $seg }{ 'score' } = $segScore;
|
|
if ( $detail >= 2 )
|
|
{
|
|
printf " $method score using 5-grams = %.4f for system \"$sys\" on segment $seg of document \"$doc\" (%d words)\n", $segScore, $tst_cnt->[1];
|
|
}
|
|
}
|
|
$cum_ref_length += $ref_length;
|
|
for (my $j=1; $j<=$max_Ngram; $j++)
|
|
{
|
|
$cum_match[$j] += $match_cnt->[$j];
|
|
$cum_tst_cnt[$j] += $tst_cnt->[$j];
|
|
$cum_ref_cnt[$j] += $ref_cnt->[$j];
|
|
$cum_tst_info[$j] += $tst_info->[$j];
|
|
$cum_ref_info[$j] += $ref_info->[$j];
|
|
}
|
|
}
|
|
return ($cum_ref_length, [@cum_match], [@cum_tst_cnt], [@cum_ref_cnt], [@cum_tst_info], [@cum_ref_info]);
|
|
}
|
|
|
|
###############################################################################################################################
|
|
# function returning the shortest reference length
|
|
# takes as input:
|
|
# - currentLength : the current (shortest) reference length
|
|
# - referenceSentenceLength : the current reference sentence length
|
|
# - candidateSentenceLength : the current candidate sentence length (unused)
|
|
###############################################################################################################################
|
|
sub brevity_penalty_shortest
|
|
{
|
|
my ( $currentLength, $referenceSentenceLength, $candidateSentenceLength ) = @_;
|
|
return ( $referenceSentenceLength < $currentLength ? $referenceSentenceLength : $currentLength );
|
|
}
|
|
|
|
###############################################################################################################################
|
|
# function returning the closest reference length (to the candidate sentence length)
|
|
# takes as input:
|
|
# - currentLength: the current (closest) reference length.
|
|
# - candidateSentenceLength : the current reference sentence length
|
|
# - candidateSentenceLength : the current candidate sentence length
|
|
# when two reference sentences are at the same distance, it will return the shortest reference sentence length
|
|
# example of 4 iterations, given:
|
|
# - one candidate sentence containing 7 tokens
|
|
# - one reference translation containing 11 tokens
|
|
# - one reference translation containing 8 tokens
|
|
# - one reference translation containing 6 tokens
|
|
# - one reference translation containing 7 tokens
|
|
# the multiple invokations will return:
|
|
# - currentLength is set to 11 (outside of this function)
|
|
# - brevity_penalty_closest( 11, 8, 7 ) returns 8, since abs( 8 - 7 ) < abs( 11 - 7 )
|
|
# - brevity_penalty_closest( 8, 6, 7 ) returns 6, since abs( 8 - 7 ) == abs( 6 - 7 ) AND 6 < 8
|
|
# - brevity_penalty_closest( 7, 6, 7 ) returns 7, since abs( 7 - 7 ) < abs( 6 - 7 )
|
|
###############################################################################################################################
|
|
sub brevity_penalty_closest
|
|
{
|
|
my ( $currentLength, $referenceSentenceLength, $candidateSentenceLength ) = @_;
|
|
my $result = $currentLength;
|
|
if ( abs( $candidateSentenceLength - $referenceSentenceLength ) <= abs( $candidateSentenceLength - $currentLength ) )
|
|
{
|
|
if ( abs( $candidateSentenceLength - $referenceSentenceLength ) == abs( $candidateSentenceLength - $currentLength ) )
|
|
{
|
|
if ( $currentLength > $referenceSentenceLength )
|
|
{
|
|
$result = $referenceSentenceLength;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
$result = $referenceSentenceLength;
|
|
}
|
|
}
|
|
return $result;
|
|
}
|
|
|
|
#################################
|
|
|
|
sub score_segment
|
|
{
|
|
my ($tst_seg, @ref_segs) = @_;
|
|
my (@tst_wrds, %tst_ngrams, @match_count, @tst_count, @tst_info);
|
|
my (@ref_wrds, $ref_seg, %ref_ngrams, %ref_ngrams_max, @ref_count, @ref_info);
|
|
my ($ngram);
|
|
my (@nwrds_ref);
|
|
my $ref_length;
|
|
|
|
for (my $j=1; $j<= $max_Ngram; $j++)
|
|
{
|
|
$match_count[$j] = $tst_count[$j] = $ref_count[$j] = $tst_info[$j] = $ref_info[$j] = 0;
|
|
}
|
|
|
|
# get the ngram counts for the test segment
|
|
@tst_wrds = split /\s+/, $tst_seg;
|
|
%tst_ngrams = %{Words2Ngrams (@tst_wrds)};
|
|
for (my $j=1; $j<=$max_Ngram; $j++)
|
|
{
|
|
# compute ngram counts
|
|
$tst_count[$j] = $j<=@tst_wrds ? (@tst_wrds - $j + 1) : 0;
|
|
}
|
|
|
|
# get the ngram counts for the reference segments
|
|
foreach $ref_seg (@ref_segs)
|
|
{
|
|
@ref_wrds = split /\s+/, $ref_seg;
|
|
%ref_ngrams = %{Words2Ngrams (@ref_wrds)};
|
|
foreach $ngram (keys %ref_ngrams)
|
|
{
|
|
# find the maximum # of occurrences
|
|
my @wrds = split / /, $ngram;
|
|
$ref_info[@wrds] += $ngram_info{$ngram};
|
|
$ref_ngrams_max{$ngram} = defined $ref_ngrams_max{$ngram} ? max ($ref_ngrams_max{$ngram}, $ref_ngrams{$ngram}) : $ref_ngrams{$ngram};
|
|
}
|
|
for (my $j=1; $j<=$max_Ngram; $j++)
|
|
{
|
|
# update ngram counts
|
|
$ref_count[$j] += $j<=@ref_wrds ? (@ref_wrds - $j + 1) : 0;
|
|
}
|
|
if ( not defined( $ref_length ) )
|
|
{
|
|
$ref_length = scalar( @ref_wrds );
|
|
}
|
|
else
|
|
{
|
|
$ref_length = &{$BLEU_BP}( $ref_length, scalar( @ref_wrds ), scalar( @tst_wrds ) );
|
|
}
|
|
}
|
|
|
|
# accumulate scoring stats for tst_seg ngrams that match ref_seg ngrams
|
|
foreach $ngram (keys %tst_ngrams)
|
|
{
|
|
next unless defined $ref_ngrams_max{$ngram};
|
|
my @wrds = split / /, $ngram;
|
|
$tst_info[@wrds] += $ngram_info{$ngram} * min($tst_ngrams{$ngram},$ref_ngrams_max{$ngram});
|
|
$match_count[@wrds] += my $count = min($tst_ngrams{$ngram},$ref_ngrams_max{$ngram});
|
|
printf "%.2f info for each of $count %d-grams = '%s'\n", $ngram_info{$ngram}, scalar @wrds, $ngram
|
|
if $detail >= 3;
|
|
}
|
|
|
|
return ($ref_length, [@match_count], [@tst_count], [@ref_count], [@tst_info], [@ref_info]);
|
|
}
|
|
|
|
#################################
|
|
|
|
sub bleu_score_nosmoothing
|
|
{
|
|
my ($ref_length, $matching_ngrams, $tst_ngrams, $sys, $SCOREmt) = @_;
|
|
my $score = 0;
|
|
my $iscore = 0;
|
|
|
|
for ( my $j = 1; $j <= $max_Ngram; ++$j )
|
|
{
|
|
if ($matching_ngrams->[ $j ] == 0)
|
|
{
|
|
$SCOREmt->{ $j }{ $sys }{ cum }=0;
|
|
}
|
|
else
|
|
{
|
|
my $len_score = min (0, 1-$ref_length/$tst_ngrams->[1]);
|
|
# Cumulative N-Gram score
|
|
$score += log( $matching_ngrams->[ $j ] / $tst_ngrams->[ $j ] );
|
|
$SCOREmt->{ $j }{ $sys }{ cum } = exp( $score / $j + $len_score );
|
|
# Individual N-Gram score
|
|
$iscore = log( $matching_ngrams->[ $j ] / $tst_ngrams->[ $j ] );
|
|
$SCOREmt->{ $j }{ $sys }{ ind } = exp( $iscore );
|
|
}
|
|
}
|
|
return $SCOREmt->{ 4 }{ $sys }{ cum };
|
|
}
|
|
|
|
###############################################################################################################################
|
|
# Default method used to compute the BLEU score, using smoothing.
|
|
# Note that the method used can be overridden using the '--no-smoothing' command-line argument
|
|
# The smoothing is computed by taking 1 / ( 2^k ), instead of 0, for each precision score whose matching n-gram count is null
|
|
# k is 1 for the first 'n' value for which the n-gram match count is null
|
|
# For example, if the text contains:
|
|
# - one 2-gram match
|
|
# - and (consequently) two 1-gram matches
|
|
# the n-gram count for each individual precision score would be:
|
|
# - n=1 => prec_count = 2 (two unigrams)
|
|
# - n=2 => prec_count = 1 (one bigram)
|
|
# - n=3 => prec_count = 1/2 (no trigram, taking 'smoothed' value of 1 / ( 2^k ), with k=1)
|
|
# - n=4 => prec_count = 1/4 (no fourgram, taking 'smoothed' value of 1 / ( 2^k ), with k=2)
|
|
###############################################################################################################################
|
|
sub bleu_score
|
|
{
|
|
my ($ref_length, $matching_ngrams, $tst_ngrams, $sys, $SCOREmt,$report_length) = @_;
|
|
my $score = 0;
|
|
my $iscore = 0;
|
|
my $exp_len_score = 0;
|
|
$exp_len_score = exp( min (0, 1 - $ref_length / $tst_ngrams->[ 1 ] ) ) if ( $tst_ngrams->[ 1 ] > 0 );
|
|
print "length ratio: ".($tst_ngrams->[1]/$ref_length)." ($tst_ngrams->[1]/$ref_length), penalty (log): ".log($exp_len_score)."\n" if $report_length;
|
|
my $smooth = 1;
|
|
for ( my $j = 1; $j <= $max_Ngram; ++$j )
|
|
{
|
|
if ( $tst_ngrams->[ $j ] == 0 )
|
|
{
|
|
$iscore = 0;
|
|
}
|
|
elsif ( $matching_ngrams->[ $j ] == 0 )
|
|
{
|
|
$smooth *= 2;
|
|
$iscore = log( 1 / ( $smooth * $tst_ngrams->[ $j ] ) );
|
|
}
|
|
else
|
|
{
|
|
$iscore = log( $matching_ngrams->[ $j ] / $tst_ngrams->[ $j ] );
|
|
}
|
|
$SCOREmt->{ $j }{ $sys }{ ind } = exp( $iscore );
|
|
$score += $iscore;
|
|
$SCOREmt->{ $j }{ $sys }{ cum } = exp( $score / $j ) * $exp_len_score;
|
|
}
|
|
return $SCOREmt->{ 4 }{ $sys }{ cum };
|
|
}
|
|
|
|
#################################
|
|
|
|
sub nist_score
|
|
{
|
|
my ($nsys, $matching_ngrams, $tst_ngrams, $ref_ngrams, $tst_info, $ref_info, $sys, $SCOREmt) = @_;
|
|
my $score = 0;
|
|
my $iscore = 0;
|
|
|
|
for (my $n=1; $n<=$max_Ngram; $n++)
|
|
{
|
|
$score += $tst_info->[$n]/max($tst_ngrams->[$n],1);
|
|
$SCOREmt->{$n}{$sys}{cum} = $score * nist_length_penalty($tst_ngrams->[1]/($ref_ngrams->[1]/$nsys));
|
|
$iscore = $tst_info->[$n]/max($tst_ngrams->[$n],1);
|
|
$SCOREmt->{$n}{$sys}{ind} = $iscore * nist_length_penalty($tst_ngrams->[1]/($ref_ngrams->[1]/$nsys));
|
|
}
|
|
return $SCOREmt->{5}{$sys}{cum};
|
|
}
|
|
|
|
#################################
|
|
|
|
sub Words2Ngrams
|
|
{
|
|
#convert a string of words to an Ngram count hash
|
|
my %count = ();
|
|
|
|
for (; @_; shift)
|
|
{
|
|
my ($j, $ngram, $word);
|
|
for ($j=0; $j<$max_Ngram and defined($word=$_[$j]); $j++)
|
|
{
|
|
$ngram .= defined $ngram ? " $word" : $word;
|
|
$count{$ngram}++;
|
|
}
|
|
}
|
|
return {%count};
|
|
}
|
|
|
|
#################################
|
|
|
|
sub tokenization
|
|
{
|
|
my ($norm_text) = @_;
|
|
|
|
# language-independent part:
|
|
$norm_text =~ s/<skipped>//g; # strip "skipped" tags
|
|
$norm_text =~ s/-\n//g; # strip end-of-line hyphenation and join lines
|
|
$norm_text =~ s/\n/ /g; # join lines
|
|
$norm_text =~ s/"/"/g; # convert SGML tag for quote to "
|
|
$norm_text =~ s/&/&/g; # convert SGML tag for ampersand to &
|
|
$norm_text =~ s/</</g; # convert SGML tag for less-than to >
|
|
$norm_text =~ s/>/>/g; # convert SGML tag for greater-than to <
|
|
|
|
# language-dependent part (assuming Western languages):
|
|
$norm_text = " $norm_text ";
|
|
$norm_text =~ tr/[A-Z]/[a-z]/ unless $preserve_case;
|
|
$norm_text =~ s/([\{-\~\[-\` -\&\(-\+\:-\@\/])/ $1 /g; # tokenize punctuation
|
|
$norm_text =~ s/([^0-9])([\.,])/$1 $2 /g; # tokenize period and comma unless preceded by a digit
|
|
$norm_text =~ s/([\.,])([^0-9])/ $1 $2/g; # tokenize period and comma unless followed by a digit
|
|
$norm_text =~ s/([0-9])(-)/$1 $2 /g; # tokenize dash when preceded by a digit
|
|
$norm_text =~ s/\s+/ /g; # one space only between words
|
|
$norm_text =~ s/^\s+//; # no leading space
|
|
$norm_text =~ s/\s+$//; # no trailing space
|
|
|
|
return $norm_text;
|
|
}
|
|
|
|
|
|
sub tokenization_international
|
|
{
|
|
my ($norm_text) = @_;
|
|
|
|
$norm_text =~ s/<skipped>//g; # strip "skipped" tags
|
|
$norm_text =~ s/\p{Hyphen}\p{Zl}//g; # strip end-of-line hyphenation and join lines
|
|
$norm_text =~ s/\p{Zl}/ /g; # join lines
|
|
|
|
# replace entities
|
|
$norm_text =~ s/"/\"/g; # quote to "
|
|
$norm_text =~ s/&/&/g; # ampersand to &
|
|
$norm_text =~ s/</</g; # less-than to <
|
|
$norm_text =~ s/>/>/g; # greater-than to >
|
|
$norm_text =~ s/'/\'/g; # apostrophe to '
|
|
|
|
$norm_text = lc( $norm_text ) unless $preserve_case; # lowercasing if needed
|
|
$norm_text =~ s/([^[:ascii:]])/ $1 /g if ( $split_non_ASCII );
|
|
|
|
# punctuation: tokenize any punctuation unless followed AND preceded by a digit
|
|
$norm_text =~ s/(\P{N})(\p{P})/$1 $2 /g;
|
|
$norm_text =~ s/(\p{P})(\P{N})/ $1 $2/g;
|
|
|
|
$norm_text =~ s/(\p{S})/ $1 /g; # tokenize symbols
|
|
|
|
$norm_text =~ s/\p{Z}+/ /g; # one space only between words
|
|
$norm_text =~ s/^\p{Z}+//; # no leading space
|
|
$norm_text =~ s/\p{Z}+$//; # no trailing space
|
|
|
|
return $norm_text;
|
|
}
|
|
|
|
#################################
|
|
|
|
sub nist_length_penalty
|
|
{
|
|
my ($ratio) = @_;
|
|
return 1 if $ratio >= 1;
|
|
return 0 if $ratio <= 0;
|
|
my $ratio_x = 1.5;
|
|
my $score_x = 0.5;
|
|
my $beta = -log($score_x)/log($ratio_x)/log($ratio_x);
|
|
return exp (-$beta*log($ratio)*log($ratio));
|
|
}
|
|
|
|
#################################
|
|
|
|
sub date_time_stamp
|
|
{
|
|
my ($sec, $min, $hour, $mday, $mon, $year, $wday, $yday, $isdst) = localtime();
|
|
my @months = qw(Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec);
|
|
my ($date, $time);
|
|
$time = sprintf "%2.2d:%2.2d:%2.2d", $hour, $min, $sec;
|
|
$date = sprintf "%4.4s %3.3s %s", 1900+$year, $months[$mon], $mday;
|
|
return ($date, $time);
|
|
}
|
|
|
|
#################################
|
|
|
|
sub extract_sgml_tag_and_span
|
|
{
|
|
my ($name, $data) = @_;
|
|
($data =~ m|<$name\s*([^>]*)>(.*?)</$name\s*>(.*)|si) ? ($1, $2, $3) : ();
|
|
}
|
|
|
|
#################################
|
|
|
|
sub extract_sgml_tag_attribute
|
|
{
|
|
my ($name, $data) = @_;
|
|
($data =~ m|$name\s*=\s*\"?([^\"]*)\"?|si) ? ($1) : ();
|
|
}
|
|
|
|
#################################
|
|
|
|
sub max
|
|
{
|
|
my ($max, $next);
|
|
|
|
return unless defined ($max=pop);
|
|
while (defined ($next=pop))
|
|
{
|
|
$max = $next if $next > $max;
|
|
}
|
|
return $max;
|
|
}
|
|
|
|
#################################
|
|
|
|
sub min
|
|
{
|
|
my ($min, $next);
|
|
|
|
return unless defined ($min=pop);
|
|
while (defined ($next=pop))
|
|
{
|
|
$min = $next if $next < $min;
|
|
}
|
|
return $min;
|
|
}
|
|
|
|
#################################
|
|
|
|
sub printout_report
|
|
{
|
|
if ( $METHOD eq "BOTH" )
|
|
{
|
|
foreach my $sys (sort @tst_sys)
|
|
{
|
|
printf "NIST score = %2.4f BLEU score = %.4f for system \"$sys\"\n",$NISTmt{5}{$sys}{cum},$BLEUmt{4}{$sys}{cum};
|
|
}
|
|
}
|
|
elsif ($METHOD eq "NIST" )
|
|
{
|
|
foreach my $sys (sort @tst_sys)
|
|
{
|
|
printf "NIST score = %2.4f for system \"$sys\"\n",$NISTmt{5}{$sys}{cum};
|
|
}
|
|
}
|
|
elsif ($METHOD eq "BLEU" )
|
|
{
|
|
foreach my $sys (sort @tst_sys)
|
|
{
|
|
printf "\nBLEU score = %.4f for system \"$sys\"\n",$BLEUmt{4}{$sys}{cum};
|
|
}
|
|
}
|
|
printf "\n# ------------------------------------------------------------------------\n\n";
|
|
printf "Individual N-gram scoring\n";
|
|
printf " 1-gram 2-gram 3-gram 4-gram 5-gram 6-gram 7-gram 8-gram 9-gram\n";
|
|
printf " ------ ------ ------ ------ ------ ------ ------ ------ ------\n";
|
|
|
|
if ( ( $METHOD eq "BOTH" ) || ($METHOD eq "NIST") )
|
|
{
|
|
foreach my $sys (sort @tst_sys)
|
|
{
|
|
printf " NIST:";
|
|
for (my $i=1; $i<=$max_Ngram; $i++)
|
|
{
|
|
printf " %2.4f ",$NISTmt{$i}{$sys}{ind}
|
|
}
|
|
printf " \"$sys\"\n";
|
|
}
|
|
printf "\n";
|
|
}
|
|
|
|
if ( ( $METHOD eq "BOTH" ) || ($METHOD eq "BLEU") )
|
|
{
|
|
foreach my $sys (sort @tst_sys)
|
|
{
|
|
printf " BLEU:";
|
|
for (my $i=1; $i<=$max_Ngram; $i++)
|
|
{
|
|
printf " %2.4f ",$BLEUmt{$i}{$sys}{ind}
|
|
}
|
|
printf " \"$sys\"\n";
|
|
}
|
|
}
|
|
|
|
printf "\n# ------------------------------------------------------------------------\n";
|
|
printf "Cumulative N-gram scoring\n";
|
|
printf " 1-gram 2-gram 3-gram 4-gram 5-gram 6-gram 7-gram 8-gram 9-gram\n";
|
|
printf " ------ ------ ------ ------ ------ ------ ------ ------ ------\n";
|
|
|
|
if (( $METHOD eq "BOTH" ) || ($METHOD eq "NIST"))
|
|
{
|
|
foreach my $sys (sort @tst_sys)
|
|
{
|
|
printf " NIST:";
|
|
for (my $i=1; $i<=$max_Ngram; $i++)
|
|
{
|
|
printf " %2.4f ",$NISTmt{$i}{$sys}{cum}
|
|
}
|
|
printf " \"$sys\"\n";
|
|
}
|
|
}
|
|
printf "\n";
|
|
if ( ( $METHOD eq "BOTH" ) || ($METHOD eq "BLEU") )
|
|
{
|
|
foreach my $sys (sort @tst_sys)
|
|
{
|
|
printf " BLEU:";
|
|
for (my $i=1; $i<=$max_Ngram; $i++)
|
|
{
|
|
printf " %2.4f ",$BLEUmt{$i}{$sys}{cum}
|
|
}
|
|
printf " \"$sys\"\n";
|
|
}
|
|
}
|
|
}
|
|
|
|
###############################################################################################################################
|
|
# Create three files, by using:
|
|
# - $prefix : the prefix used for the output file names
|
|
# - %overall : a hash containing seg/doc/sys-level scores:
|
|
# - $overall{ $SYSTEM_ID }{ 'score' } => system-level score
|
|
# - $overall{ $SYSTEM_ID }{ 'documents' }{ $DOCUMENT_ID }{ 'score' } => document-level score
|
|
# - $overall{ $SYSTEM_ID }{ 'documents' }{ $DOCUMENT_ID }{ 'segments' }{ $SEGMENT_ID } => segment-level score
|
|
###############################################################################################################################
|
|
sub outputMetricsMATR
|
|
{
|
|
my ( $prefix, %overall ) = @_;
|
|
my $fileNameSys = $prefix . '-sys.scr';
|
|
my $fileNameDoc = $prefix . '-doc.scr';
|
|
my $fileNameSeg = $prefix . '-seg.scr';
|
|
open FILEOUT_SYS, '>', $fileNameSys or die "Could not open file: ${fileNameSys}";
|
|
open FILEOUT_DOC, '>', $fileNameDoc or die "Could not open file: ${fileNameDoc}";
|
|
open FILEOUT_SEG, '>', $fileNameSeg or die "Could not open file: ${fileNameSeg}";
|
|
foreach my $sys ( sort( keys( %overall ) ) )
|
|
{
|
|
my $scoreSys = $overall{ $sys }{ 'score' };
|
|
print FILEOUT_SYS "${tst_id}\t${sys}\t${scoreSys}\n";
|
|
foreach my $doc ( sort( keys( %{$overall{ $sys }{ 'documents' }} ) ) )
|
|
{
|
|
my $scoreDoc = $overall{ $sys }{ 'documents' }{ $doc }{ 'score' };
|
|
print FILEOUT_DOC "${tst_id}\t${sys}\t${doc}\t${scoreDoc}\n";
|
|
foreach my $seg ( sort{ $a <=> $b }( keys( %{$overall{ $sys }{ 'documents' }{ $doc }{ 'segments' }} ) ) )
|
|
{
|
|
my $scoreSeg = $overall{ $sys }{ 'documents' }{ $doc }{ 'segments' }{ $seg }{ 'score' };
|
|
print FILEOUT_SEG "${tst_id}\t${sys}\t${doc}\t${seg}\t${scoreSeg}\n";
|
|
}
|
|
}
|
|
}
|
|
close FILEOUT_SEG;
|
|
close FILEOUT_DOC;
|
|
close FILEOUT_SYS;
|
|
}
|
|
|