UdS-Sant: English–German Hybrid Machine Translation System
By Santanu Pal, Sudip Kumar Naskar, Josef van Genabith. 2015
14 citations recorded by the source corpus.
This paper describes the UdS-Sant English‐German Hybrid Machine Translation (MT) system submitted to the Translation Task organized in the Workshop on Statistical Machine Translation (WMT) 2015. Our proposed hybrid system brings improvements over the baseline system by incorporating additional knowledge such as extracted bilingual named entities and bilingual phrase pairs induced from example-based methods. The reported final submission is the result of a hybrid system obtained from confusion network based system combination that combines the best performance of each individual system in a multi-engine pipeline.
Subfields: Artificial Intelligence, Machine Translation
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Citations in the corpus
- Findings of the 2015 Workshop on Statistical Machine Translation (2015, neutral): “After pruning, the final stage of the APE pipeline tries to raise the capability of the decoder to select the correct translation rule by the introduction of new task specific features integrated in (Pal et al., 2015b) Table 19: Participants in the WMT15 Automatic Post-editing pilot task. the model.”
- JU-USAAR: A Domain Adaptive MT System (2016, methodology): “We combined all data and performed cleaning in two steps: (i) Cleaning-1: following the cleaning process described in (Pal et al., 2015), and (ii) Cleaning 2: using the Moses (Koehn et al., 2007) corpus cleaning scripts with minimum and maximum number of tokens set to 1 and 80 respectively.”