CfP: Machine Translation Journal Special Issue on Human Factors in Neural Machine Translation

Guest editors:
• Sheila Castilho (Dublin City University/ADAPT Centre)
• Federico Gaspari (University for Foreigners “Dante Alighieri” of Reggio Calabria/ADAPT Centre)
• Joss Moorkens (Dublin City University/ADAPT Centre)
• Maja Popović (Humboldt Universität zu Berlin)
• Antonio Toral (University of Groningen)

Since the Machine Translation (MT) community became aware of the potential of Neural Machine Translation (NMT), an increasing number of MT providers and research groups have focused their energies and resources on developing NMT systems. More and more NMT systems continue to go into production, providing consumers of raw MT with output that shows a jump in fluency when compared with statistical MT (SMT; Bentivogli et al. 2017; Toral and Sánchez-Cartagena 2017). However, it is not yet clear how translators can best work with NMT output, whether there are advantages to using NMT as a productivity tool, or what specific challenges are involved in post-editing NMT output with respect to SMT. Studies (such as Castilho et al. 2017) showed minor improvements in productivity and technical effort, relative to the improved scores using automatic metrics and human fluency evaluation.

This special issue seeks to publish studies that investigate how users work with NMT output, in order to understand the repercussions of the large-scale move to NMT on translators and post-editors.

Areas of special interest include, but are not limited to, the following:

* Post-editing techniques and approaches specific to NMT output
* Usability studies
* Users and interactive NMT (see Peris and Casacuberta 2018)
* Controlled languages designed to optimise the result of NMT
* Error taxonomies to evaluate and improve NMT systems (Klubička et al., 2017)
* Studies of cognitive effort (possibly using eye-tracking or pause analysis)
* Studies of technical and temporal effort in MT interaction
* Hybrid forms of NMT (combined with rule-based or statistical approaches)
* Integrating user feedback in NMT systems (see Turchi et al. 2017)
* Controlling terminology in NMT systems

CPF: https://www.springer.com/computer/ai/journal/10590/PSE...

IMPORTANT DATES:
July 15, 2018: Paper submission due
August 30, 2018: Notification of acceptance
October 10, 2018: Camera ready paper due

SUBMISSION GUIDELINES:
• Authors should follow the "Instructions for Authors" available on the journal website:
o Go to https://link.springer.com/journal/10590
o Click on ‘Instructions for authors’ on the right
o Expand ‘Text’ and you will see a Latex template
• Length of paper is determined by total of submissions received. We recommend around 15 pages.
• Papers should be submitted online directly on the MT journal's submission website: http://www.editorialmanager.com/coat/default.asp and select this special issue

https://www.springer.com/computer/ai/journal/10590/PSE?detailsPage=press