**** Apologies for cross -posting ****

*SECOND CALL FOR PAPERS:* 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?detailsPage=press

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

*SUBMISSION GUIDELINES:*
o 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
o 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
---


*Sheila Castilho* | Post-Doctoral Researcher
ADAPT Centre


Dublin City University p: +353 (0) 1 700 6719 <(01)%20700%206719>
Dublin  e: [email protected]
Ireland www.adaptcentre.ie

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