voice_clone_v3 / transformers /examples /legacy /seq2seq /romanian_postprocessing.md
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Motivation

Without processing, english-> romanian mbart-large-en-ro gets BLEU score 26.8 on the WMT data. With post processing, it can score 37.. Here is the postprocessing code, stolen from @mjpost in this issue

Instructions

Note: You need to have your test_generations.txt before you start this process. (1) Setup mosesdecoder and wmt16-scripts

cd $HOME
git clone git@github.com:moses-smt/mosesdecoder.git
cd mosesdecoder  
git clone git@github.com:rsennrich/wmt16-scripts.git

(2) define a function for post processing. It removes diacritics and does other things I don't understand

ro_post_process () {
  sys=$1
  ref=$2
  export MOSES_PATH=$HOME/mosesdecoder
  REPLACE_UNICODE_PUNCT=$MOSES_PATH/scripts/tokenizer/replace-unicode-punctuation.perl
  NORM_PUNC=$MOSES_PATH/scripts/tokenizer/normalize-punctuation.perl
  REM_NON_PRINT_CHAR=$MOSES_PATH/scripts/tokenizer/remove-non-printing-char.perl
  REMOVE_DIACRITICS=$MOSES_PATH/wmt16-scripts/preprocess/remove-diacritics.py
  NORMALIZE_ROMANIAN=$MOSES_PATH/wmt16-scripts/preprocess/normalise-romanian.py
  TOKENIZER=$MOSES_PATH/scripts/tokenizer/tokenizer.perl



  lang=ro
  for file in $sys $ref; do
    cat $file \
    | $REPLACE_UNICODE_PUNCT \
    | $NORM_PUNC -l $lang \
    | $REM_NON_PRINT_CHAR \
    | $NORMALIZE_ROMANIAN \
    | $REMOVE_DIACRITICS \
    | $TOKENIZER -no-escape -l $lang \
    > $(basename $file).tok
  done
  # compute BLEU
  cat $(basename $sys).tok | sacrebleu -tok none -s none -b $(basename $ref).tok
}

(3) Call the function on test_generations.txt and test.target For example,

ro_post_process enro_finetune/test_generations.txt wmt_en_ro/test.target

This will split out a new blue score and write a new fine called test_generations.tok with post-processed outputs.