Datasets › HumanMT
HumanMT
HumanMT is a collection of human ratings and corrections of machine translations. It consists of two parts: The first part contains five-point and pairwise sentence-level ratings, the second part contains error markings and corrections. Details are described in the following.
I. Sentence-level ratings This is a collection of five-point and pairwise ratings for 1000 German-English machine translations of TED talks (IWSLT 2014). The ratings were collected with the purpose of assessing machine translation quality rating reliability and learnability to improve a neural machine translation model with human reinforcement (see publications).
II. Error markings and corrections This is a collection of word-level error markings and post-edits/corrections for 3120 English-German machine translated sentences of 30 selected TED talks (IWSLT 2017). Each sentence received either a correction or a marking of errors from human annotators. This data was collected with the purpose of comparing annotation cost and quality, and potential for downstream machine translation improvements between annotation modes (see publications).
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- HumanMT
1 variant name, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections