A Grain of Salt for the WMT Manual Evaluation

The Workshop on Statistical Machine Translation (WMT) has become one of ACL's flagship workshops, held annually since 2006. In addition to soliciting papers from the research community, WMT also features a shared translation task for evaluating MT systems. This shared task is notable for having manual evaluation as its cornerstone. The Workshop's overview paper, playing a descriptive and administrative role, reports the main results of the evaluation without delving deep into analyzing those results. The aim of this paper is to investigate and explain some interesting idiosyncrasies in the reported results, which only become apparent when performing a more thorough analysis of the collected annotations. Our analysis sheds some light on how the reported results should (and should not) be interpreted, and also gives rise to some helpful recommendation for the organizers of WMT

CUNI in WMT14: Chimera Still Awaits Bellerophon

We present our English→Czech and English→Hindi submissions for this year’s WMT translation task. For English→Czech, we build upon last year’s CHIMERA and evaluate several setups. English→Hindi is a new language pair for this year. We experimented with reverse self-training to acquire more (synthetic) parallel data and with modeling target-side morphology

Using MT-ComparEval

The paper showcases the MT-ComparEval tool for qualitative evaluation of machine translation (MT). MT-ComparEval is an opensource tool that has been designed in order to help MT developers by providing a graphical user interface that allows the comparison and evaluation of different MT engines/experiments and settings

TectoMT – a deep-­linguistic core of the combined Chimera MT system

Chimera is a machine translation system that combines the TectoMT deep-linguistic core with phrase-based MT system Moses. For English–Czech pair it also uses the Depfix post-correction system. All the components run on Unix/Linux platform and are open source (available from Perl repository CPAN and the LINDAT/CLARIN repository). The main website is https://ufal.mff.cuni.cz/tectomt. The development is currently supported by the QTLeap 7th FP project (http://qtleap.eu)

Dictionary-based Domain Adaptation of MT Systems without Retraining

We describe our submission to the IT-domain translation task of WMT 2016. We perform domain adaptation with dictionary data on already trained MT systems with no further retraining. We apply our approach to two conceptually different systems developed within the QTLeap project: TectoMT and Moses, as well as Chimera, their combination. In all settings, our method improves the translation quality. Moreover, the basic variant of our approach is applicable to any MT system, including a black-box one

Impacts of climate change adaptation options on soil functions: A review of European case‐studies

Soils are vital for supporting food security and other ecosystem services. Climate change can affect soil functions both directly and indirectly. Direct effects include temperature, precipitation, and moisture regime changes. Indirect effects include those that are induced by adaptations such as irrigation, crop rotation changes, and tillage practices. Although extensive knowledge is available on the direct effects, an understanding of the indirect effects of agricultural adaptation options is less complete. A review of 20 agricultural adaptation case‐studies across Europe was conducted to assess implications to soil threats and soil functions and the link to the Sustainable Development Goals (SDGs). The major findings are as follows: (a) adaptation options reflect local conditions; (b) reduced soil erosion threats and increased soil organic carbon are expected, although compaction may increase in some areas; (c) most adaptation options are anticipated to improve the soil functions of food and biomass production, soil organic carbon storage, and storing, filtering, transforming, and recycling capacities, whereas possible implications for soil biodiversity are largely unknown; and (d) the linkage between soil functions and the SDGs implies improvements to SDG 2 (achieving food security and promoting sustainable agriculture) and SDG 13 (taking action on climate change), whereas the relationship to SDG 15 (using terrestrial ecosystems sustainably) is largely unknown. The conclusion is drawn that agricultural adaptation options, even when focused on increasing yields, have the potential to outweigh the negative direct effects of climate change on soil degradation in many European regions

Findings of the 2022 Conference on Machine Translation (WMT22)

International audienceThis paper presents the results of the General Machine Translation Task organised as part of the Conference on Machine Translation (WMT) 2022. In the general MT task, participants were asked to build machine translation systems for any of 11 language pairs, to be evaluated on test sets consisting of four different domains. We evaluate system outputs with human annotators using two different techniques: reference-based direct assessment and (DA) and a combination of DA and scalar quality metric (DA+SQM)