blob: 3a968a5d1d67cec9e48a7eae25b961d65b7a435b (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
|
#!/bin/bash -v
# suffix of source language files
SRC=en
# suffix of target language files
TRG=de
# number of merge operations
bpe_operations=32000
# path to moses decoder: https://github.com/moses-smt/mosesdecoder
mosesdecoder=../tools/moses-scripts
# path to subword segmentation scripts: https://github.com/rsennrich/subword-nmt
subword_nmt=../tools/subword-nmt
# tokenize
for prefix in corpus valid test2014 test2015 test2016
do
cat data/$prefix.$SRC \
| $mosesdecoder/scripts/tokenizer/normalize-punctuation.perl -l $SRC \
| $mosesdecoder/scripts/tokenizer/tokenizer.perl -a -l $SRC > data/$prefix.tok.$SRC
test -f data/$prefix.$TRG || continue
cat data/$prefix.$TRG \
| $mosesdecoder/scripts/tokenizer/normalize-punctuation.perl -l $TRG \
| $mosesdecoder/scripts/tokenizer/tokenizer.perl -a -l $TRG > data/$prefix.tok.$TRG
done
# clean empty and long sentences, and sentences with high source-target ratio (training corpus only)
mv data/corpus.tok.$SRC data/corpus.tok.uncleaned.$SRC
mv data/corpus.tok.$TRG data/corpus.tok.uncleaned.$TRG
$mosesdecoder/scripts/training/clean-corpus-n.perl data/corpus.tok.uncleaned $SRC $TRG data/corpus.tok 1 100
# train truecaser
$mosesdecoder/scripts/recaser/train-truecaser.perl -corpus data/corpus.tok.$SRC -model model/tc.$SRC
$mosesdecoder/scripts/recaser/train-truecaser.perl -corpus data/corpus.tok.$TRG -model model/tc.$TRG
# apply truecaser (cleaned training corpus)
for prefix in corpus valid test2014 test2015 test2016
do
$mosesdecoder/scripts/recaser/truecase.perl -model model/tc.$SRC < data/$prefix.tok.$SRC > data/$prefix.tc.$SRC
test -f data/$prefix.tok.$TRG || continue
$mosesdecoder/scripts/recaser/truecase.perl -model model/tc.$TRG < data/$prefix.tok.$TRG > data/$prefix.tc.$TRG
done
# train BPE
cat data/corpus.tc.$SRC data/corpus.tc.$TRG | $subword_nmt/learn_bpe.py -s $bpe_operations > model/$SRC$TRG.bpe
# apply BPE
for prefix in corpus valid test2014 test2015 test2016
do
$subword_nmt/apply_bpe.py -c model/$SRC$TRG.bpe < data/$prefix.tc.$SRC > data/$prefix.bpe.$SRC
test -f data/$prefix.tc.$TRG || continue
$subword_nmt/apply_bpe.py -c model/$SRC$TRG.bpe < data/$prefix.tc.$TRG > data/$prefix.bpe.$TRG
done
|