The DOI matches its OpenAlex record; 5 of the 5 references it cites were found in a registry or an index.
An Evaluation Tool for Machine Translation: Fast Evaluation for MT Research
Open accessAbstract
In this paper we present a tool for the evaluation of translation quality.First, the typical requirements of such a tool in the framework of machine translation (MT) research are discussed.We define evaluation criteria which are more adequate than pure edit distance and we describe how the measurement along these quality criteria is performed semi-automatically in a fast, convenient and above all consistent way using our tool and the corresponding graphical user interface.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Accelerated DP based search for statistical translation
Tillmann, C., Vogel, S., Ney, H., Zubiaga, A., & Sawaf, H. (1997) · 5th European Conference on Speech Communication and Technology (Eurospeech 1997) · doi:10.21437/eurospeech.1997-673 · Cited by 232
Self-citationFinite-state speech-to-speech translation
Vidal, E. (2002) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1997.599563 · Cited by 137
Verbmobil : translation of face-to-face dialogs
Wahlster, W. (1993) · doi:10.22028/d291-24923 · Cited by 136
A DP based search algorithm for statistical machine translation
Nießen, S., Vogel, S., Ney, H., & Tillmann, C. (1998) · Annual Meeting of the Association for Computational Linguistics (ACL) · doi:10.3115/980691.980727 · Cited by 58
Self-citationA task-oriented evaluation metric for machine translation
White, J. S., & Taylor, K. B. (1998) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/2xr5dvagicuq · Cited by 25
Cited by
Minimum error rate training in statistical machine translation
Och, F. J. (2003) · Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - ACL '03 · doi:10.3115/1075096.1075117 · Cited by 2,725
Self-citationNatural language processing: state of the art, current trends and challenges
Khurana, D., Koli, A., Khatter, K., & Singh, S. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13428-4 · Cited by 1,823
Lin, C.-Y., & Och, F. J. (2004) · Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04 · doi:10.3115/1218955.1219032 · Cited by 737
Self-citation(2004) · doi:10.3115/1220355.1220427 · Cited by 294
Self-citationEvaluation of Text Generation: A Survey
Celikyilmaz, A., Clark, E., & Gao, J. (2020) · arXiv · doi:10.48550/arxiv.2006.14799 · Cited by 207
Metadata
- Authors
- Nießen, S., Och, F. J., Leusch, G., & Ney, H.
- Venue
- Language Resources and Evaluation Conference (LREC)
- Published
- 2000-05-01
- OpenAlex
- W1529616844
- Cited by
- 280
- References
- 5
- FWCI
- 9.02
- Type
- conference paper
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An Evaluation Tool for Machine Translation: Fast Evaluation for MT Research. https://app.cochat.ai/papers/10.63317/56t9t4rchhar
- The paper
- Nießen, S., Och, F. J., Leusch, G., & Ney, H. (2000). An Evaluation Tool for Machine Translation: Fast Evaluation for MT Research. Language Resources and Evaluation Conference (LREC). https://doi.org/10.63317/56t9t4rchhar
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
