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Hjerson: An Open Source Tool for Automatic Error Classification of Machine Translation Output

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Hjerson: A tool for automatic error classification

By: Maja Popovic [email protected], August 2011

Hjerson detects translation errors using WER alignment and RPER (reference PER) and HPER (hypotheses PER) errors. It is written in Python, so you have to install Python 2 or Python 3.

The following five error classes are supported:

  • inflectional (morphological) errors, i.e. incorrect word forms
  • reordering errors, i.e. incorrect word order
  • missing words
  • extra words
  • lexical errors, i.e. incorrect lexical choice

The option -h, --help outputs a description of the available command line options.

The required inputs are:

  • translation reference and hypothesis
  • base forms of translation reference and hypothesis

If any additional information at the word level is available (such as POS tags), it is possible to incorporate it as well in order to obtain more detals.

The required format of all inputs is tokenised (and preferably true-cased) raw text containing one sentence per line.

In the case of multiple references, all available reference sentences must be separated by the symbol #.

The default output are overall (document level) raw error counts and error rates (counts normalised over the reference or hypothesis length) for each of the five error classes.

Optional outputs are:

-s, --sent  sentence-errors.txt
    raw error counts and error rates at the sentence level are written
    in "sentence-errors.txt"

-c, --cats  categories.txt
    Original reference and hypothesis words labelled with a
    corresponding error class are written in "categories.txt"

-m, --html  categories.html
    Original reference and hypothesis words with coloured errors in
    HTML format.

If the additional information is used, only "categories.txt" and "categories.html" will be different.

Example for testing:

You can try the tool on the given example using example.ref and example.ref.base as reference inputs along with example.hyp and example.hyp.base as hypothesis inputs.

If you want to try additional information, you can use reference and hypothesis POS tags example.ref.pos and example.hyp.pos.

Then you can compare obtained files with example.totalerrorrates, example.senterrorrates, example.(pos.)cats and example.(pos.)html.

Attribution

Publications of results obtained through the use of original or
modified versions of the software have to cite the authors by referring
to the following publication:

Maja Popović: "Hjerson: An Open Source Tool for Automatic Error
Classification of Machine Translation Output". The Prague Bulletin of
Mathematical Linguistics No. 96, pp. 59--68, October 2011

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