CALL FOR PAPERS: Machine Translation Journal Special Issue on Machine Translation for Low-Resource Languages https://www.springer.com/computer/ai/journal/10590/
GUEST EDITORS • Chao-Hong Liu (ADAPT Centre/Dublin City University) • Alina Karakanta (FBK-Fondazione Bruno Kessler) • Jonathan Washington (Swarthmore College) • Xiaobing Zhao (Minzu University of China) Machine translation (MT) technologies have been improved significantly in the last two decades, with developments in phrase-based statistical MT (SMT) and recently neural MT (NMT). However, most of these methods rely on the availability of large parallel data for training the MT systems, resources which are not available for the majority of language pairs. Therefore, developing MT technologies using relatively small corpora presents a major challenge for low-resource languages. In addition, many methods for developing MT systems still rely on several natural language processing (NLP) tools to pre-process texts in source languages and post-process MT outputs in target languages. In many MT systems, the performance of these tools has a great impact on the quality of the resulting translation. This special issue solicits original research papers on MT systems/methods and related NLP tools for low-resource languages in general. Summary papers on MT research for specific low-resource languages, as well as extended versions (>40% difference) of published papers from relevant conferences/workshops are also welcome. Topics of the special issue include but are not limited to: * Research and review papers of MT systems/methods for low-resource languages * Research and review papers of pre-processing and/or post-processing NLP tools for MT * Word tokenizers/de-tokenizers for low-resource languages * Word/morpheme segmenters for low-resource languages * Use of morphology analyzers and/or morpheme segmenters in MT * Multilingual/cross-lingual NLP tools for MT * Review of available corpora of low-resource languages for MT * Pivot MT for low-resource languages * Zero-shot MT for low-resource languages * Fast building of MT systems for low-resource languages * Re-usability of existing MT systems and/or NLP tools for low-resource languages * Machine translation for language preservation IMPORTANT DATES November 26, 2019: Expression of interest (EOI) February 25, 2020: Submission deadline July 7, 2020: Camera-ready papers due December, 2020: Publication SUBMISSION GUIDELINES o Authors should follow the "Instructions for Authors" on the MT journal website o Go to https://link.springer.com/journal/10590 o Recommended length of paper is 15 pages o Papers should be submitted online on the journal's submission website via selecting this special issue *Prof. Andy Way* Deputy Director, ADAPT Centre School of Computing p: +353 1 700 5074 Dublin City University m: +353 87 221 4890 Dublin 9 e: andy....@adaptcentre.ie <em...@adaptcentre.ie> Ireland www.computing.dcu.ie/~away <http://www.adaptcentre.ie/> <https://twitter.com/adaptcentre> <https://www.facebook.com/ADAPTCentre?fref=ts> <https://www.youtube.com/channel/UC9--qVutTtyLyhZCJR7rY5g> <https://www.linkedin.com/company/adapt-centre> *A World-Leading SFI Research Centre*
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