The JULIE LAB MANTRA System for the CLEF-ER 2013 Challenge

After assessing the quality of the corpus for two language pairs (English/French and English/Spanish) we use the Moses package to train a statistical machine translation model

For the latter, we provide details on the corpus construction, insights on the data and their utilization for the biomedical task (Bojar et al., 2016; Jimeno Yepes et al., 2017) of

Achraf, O., Mohamed J.: Designing High Accuracy Statistical Machine Translation for Sign Language Using Parallel Corpus—Case study English and American Sign Language. Goyal,

With this challenge we created a basis for interesting discussions and hope to have taken the       NLP community for German text understanding a step further. .. For the challenge,

Finally, given a target citation, different MeSH headings were ranked according to the SVM prediction score of each classifier, and the top K MeSH headings were returned as

The corpora have been selected from different resources and for the purpose to serve two objectives: (1) enabling extraction of novel terms for the multi- lingual TR as part of

It uses a selection cost which integrates notably a DNN-based prosodic prediction and also a specific score to deal with narrative/direct speech parts.. Unit selection is based on

We utilized two corpora in our experiments: the Quaero medical corpus, a French annotated resource for medical entity recognition and normalization [3], which was the basis for