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# Automatic MT Error Analysis: Hjerson Helping Addicter

**Authors:** Jan Berka, [Ondřej Bojar](https://md.mova.elamur.ai/free/en/docs/papers/authors/ondrej-bojar/), [Mark Fishel](https://md.mova.elamur.ai/free/en/docs/papers/authors/mark-fishel/), [Maja Popović](https://md.mova.elamur.ai/free/en/docs/papers/authors/maja-popovic/), [Daniel Zeman](https://md.mova.elamur.ai/free/en/docs/papers/authors/daniel-zeman/) · **Year:** 2012 · **Venue:** Eighth International Conference on Language Resources and Evaluation (LREC 2012) **Link:** [aclanthology.org/L12-1160](https://aclanthology.org/L12-1160/) · **Licence:** [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) — summary only

[**12** citations](https://openalex.org/works?filter=cites:W2251919075) openalex · 2026-10-19[**5** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/berka-2012-automatic-mt-error-analysis-hjerson/) of the 140673 papers whose bibliographies we read[Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)](https://aclanthology.org/volumes/L12-1/)[licence](https://creativecommons.org/licenses/by-nc/4.0/)

- [Publisher's page](https://aclanthology.org/L12-1160/)
- [PDF](https://aclanthology.org/L12-1160.pdf)
- [DOI 10.63317/4vvqg5vs7xyw](https://doi.org/10.63317/4vvqg5vs7xyw)
- [OpenAlex](https://openalex.org/W2251919075)

**Authors (5)**

1. [Jan Berka](https://openalex.org/A5002859965) [Semantic Scholar](https://www.semanticscholar.org/author/50159903) · h 4 · 69 citations · 9 works
2. [Ondřej Bojar](https://openalex.org/A5077746237) [ORCID](https://orcid.org/0000-0002-0606-0050) · [Semantic Scholar](https://www.semanticscholar.org/author/143832874) · h 38 · 13669 citations · 364 works
3. [Mark Fishel](https://openalex.org/A5113712910) [ORCID](https://orcid.org/0000-0003-1932-2600) · [Semantic Scholar](https://www.semanticscholar.org/author/2032659) · h 17 · 1750 citations · 134 works
4. [Maja Popović](https://openalex.org/A5045306408) [ORCID](https://orcid.org/0000-0001-8234-8745) · [Semantic Scholar](https://www.semanticscholar.org/author/2487502) · h 22 · 2989 citations · 119 works
5. [Daniel Zeman](https://openalex.org/A5061392927) [ORCID](https://orcid.org/0000-0002-5791-6568) · [Semantic Scholar](https://www.semanticscholar.org/author/1771298) · h 28 · 4506 citations · 176 works

Citations and author metrics from openalex (2026-10-19); authors with the same name are not always told apart.

## What it is about

The paper presents an open-source tool for detailed MT error analysis. It joins two systems: Hjerson, the automatic classifier from Popović (2011), and Addicter, which brings alignment, a web interface and a corpus browser. Errors are found by comparing the output with the reference through a chosen word alignment, and then classed as morphological, reordering, missing, extra or lexical. Several alignments are built in (WER, longest common subsequence, a greedy injective alignment, and an HMM alignment), and the user can supply others, for example GIZA++ output or a "via-source" alignment that chains reference-to-source and source-to-hypothesis links. The interface shows an error summary table, a test-data browser where errors are coloured sentence by sentence, and a word explorer. The authors stress that alignment quality decides the classes: a bad alignment turns one lexical error into a pair of missing and extra words. Hjerson cannot separate wrong lexical choice from untranslated words without the source, which Addicter shows as a separate "other mismatch" class.

## Ideas

- I1. The alignment choice is part of the result. For the translator's Hebrew reader, which aligns words with IBM Model 1, run the error counts with two alignments (for example LCS and an HMM-style one) and report both, as Addicter does, so that the error counts show their dependence on the alignment.
- I2. Compose alignments instead of building a new aligner. Chain the reader's Hebrew-to-meta alignment with the meta-to-English links of the lexicon in `tools/translate/src/meta.rs`, which gives a Hebrew-to-English alignment for error counts, in the spirit of the via-source option.
- I3. Build a static HTML report from the Rust side with a per-class count table that links to verses, so that the residual can be checked by eye. The paper's summary-to-browser link is the model.
- I4. The source is available to the translator, so it can separate wrong lexical choice from untranslated words, which the paper's tool could not. Report that split as a feature of the Mova measure.

## For Mova

The code is `tools/translate/src/measure.rs` and a report generator in `tools/translate`. The alignment dependence is the translator's own problem, since the meta-world is built on alignments, so the paper's advice to measure with more than one alignment applies directly. The browser idea suits the residual review, where a number is only useful if the verse behind it can be opened.

Topics: [Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/topics/machine-translation/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.63317/4vvqg5vs7xyw](https://doi.org/10.63317/4vvqg5vs7xyw)

```
@inproceedings{berka2012automatic,
  title = {{Automatic MT Error Analysis: Hjerson Helping Addicter}},
  author = {Berka, Jan and Bojar, Ondřej and Fishel, Mark and Popović, Maja and Zeman, Daniel},
  booktitle = {Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  doi = {10.63317/4vvqg5vs7xyw},
  url = {https://doi.org/10.63317/4vvqg5vs7xyw}
}
```

- [← previous Letters Concerning Poetical Translations, and Virgil's and Milton's Arts of Verse](https://md.mova.elamur.ai/free/en/docs/papers/benson-1739-letters-concerning-poetical-translations/)
- [next → Biblical translation: do different strategies produce divergent texts?](https://md.mova.elamur.ai/free/en/docs/papers/bertos-2023-biblical-translation-do-different-strategies/)
- [↑ back to Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/mtrans/)

## References

15 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Ondřej Bojar. 2011. Analyzing Error Types in English-Czech Machine Translation. Prague Bulletin of Mathematical Linguistics, 95:63–76, March. [find](https://scholar.google.com/scholar?q=Ondr%CC%8Cej+Bojar%2E+2011%2E+Analyzing+Error+Types+in+English%2DCzech+Machine+Translation%2E+Prague+Bulletin+of+Mathematical+Linguistics%2C+95%3A63%E2%80%9376%2C+March%2E)
2. Michael Denkowski and Alon Lavie. 2011. Meteor 1.3: Automatic Metric for Reliable Optimization and Evaluation of Machine Translation Systems. In Proceedings of the EMNLP 2011 Workshop on Statistical Machine Translation. [find](https://scholar.google.com/scholar?q=Michael+Denkowski+and+Alon+Lavie%2E+2011%2E+Meteor+1%2E3%3A+Automatic+Metric+for+Reliable+Optimization+and+Evaluation+of+Machine+Translation+Systems%2E+In+Proceedings+of+the+EMNLP+2011+Workshop+on+Statistical+M)
3. Mark Fishel, Ondřej Bojar, Daniel Zeman, and Jan Berka. 2011. Automatic Translation Error Analysis. In Text, Speech and Dialogue: 14th International Conference, TSD 2011, volume LNAI 3658. Springer Verlag, September. [http://www-i6.informatik.rwth-aachen.de/web/Software/EvalTrans/index.html](http://www-i6.informatik.rwth-aachen.de/web/Software/EvalTrans/index.html) [↗](http://www-i6.informatik.rwth-aachen.de/web/Software/EvalTrans/index.html)
4. Mark Fishel, Ondřej Bojar, and Maja Popović. 2012. Terra: a Collection of Translation Error-Annotated Corpora. In International Conference on Language Resources and Evaluation, Istanbul, Turkey, May. [find](https://scholar.google.com/scholar?q=Mark+Fishel%2C+Ondr%CC%8Cej+Bojar%2C+and+Maja+Popovic%CC%81%2E+2012%2E+Terra%3A+a+Collection+of+Translation+Error%2DAnnotated+Corpora%2E+In+International+Conference+on+Language+Resources+and+Evaluation%2C+Istanbul%2C+Turkey%2C+May)
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7. Phillip Koehn. 2010. An Experimental Management System. The Prague Bulletin of Mathematical Linguistics, 94. [find](https://scholar.google.com/scholar?q=Phillip+Koehn%2E+2010%2E+An+Experimental+Management+System%2E+The+Prague+Bulletin+of+Mathematical+Linguistics%2C+94%2E)
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9. Nitin Madnani. 2011. iBLEU: Interactively Debugging & Scoring Statistical Machine Translation Systems. In Proceedings of the Fifth IEEE International Conference on Semantic Computing. [find](https://scholar.google.com/scholar?q=Nitin+Madnani%2E+2011%2E+iBLEU%3A+Interactively+Debugging+%26+Scoring+Statistical+Machine+Translation+Systems%2E+In+Proceedings+of+the+Fifth+IEEE+International+Conference+on+Semantic+Computing%2E)
10. Sonja Nießen, Franz Josef Och, Gregor Leusch, and Hermann Ney. 2000. An evaluation tool for machine translation: Fast evaluation for mt research. In Proceedings of the 2nd International Conference on Language Resources and Evaluation, pages 39–45, Athens, Greece, May-June. [find](https://scholar.google.com/scholar?q=Sonja+Nie%C3%9Fen%2C+Franz+Josef+Och%2C+Gregor+Leusch%2C+and+Hermann+Ney%2E+2000%2E+An+evaluation+tool+for+machine+translation%3A+Fast+evaluation+for+mt+research%2E+In+Proceedings+of+the+2nd+International+Conference+on+)
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12. Maja Popović. 2011. Hjerson: An open source tool for automatic error classification of machine translation output. The Prague Bulletin of Mathematical Linguistics, pages 59–68. [find](https://scholar.google.com/scholar?q=Maja+Popovic%CC%81%2E+2011%2E+Hjerson%3A+An+open+source+tool+for+automatic+error+classification+of+machine+translation+output%2E+The+Prague+Bulletin+of+Mathematical+Linguistics%2C+pages+59%E2%80%9368%2E)
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14. Daniel Zeman, Mark Fishel, Jan Berka, and Ondřej Bojar. 2011. Addicter: What is wrong with my translations? The Prague Bulletin of Mathematical Linguistics, 96:79– 88. [find](https://scholar.google.com/scholar?q=Daniel+Zeman%2C+Mark+Fishel%2C+Jan+Berka%2C+and+Ondr%CC%8Cej+Bojar%2E+2011%2E+Addicter%3A+What+is+wrong+with+my+translations%3F+The+Prague+Bulletin+of+Mathematical+Linguistics%2C+96%3A79%E2%80%93+88%2E)
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