36.1365, Calls: Linguistica Antverpiensia - "Human-centered augmented machine translation" (Jrnl)

Fri Apr 25 22:05:02 UTC 2025

LINGUIST List: Vol-36-1365. Fri Apr 25 2025. ISSN: 1069 - 4875.

Subject: 36.1365, Calls: Linguistica Antverpiensia  - "Human-centered augmented machine translation" (Jrnl)

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Date: 23-Apr-2025
From: Vicent Briva Iglesias [vicent.brivaiglesias at dcu.ie]
Subject: Linguistica Antverpiensia  - "Human-centered augmented machine translation" (Jrnl)

Journal: Linguistica Antverpiensia
Issue: Human-centered augmented machine translation
Call Deadline: 01-May-2025

Call for Papers:
Recent language technology developments have disrupted the translation
and interpreting professions. However, the focus has been on using
more computational power and training larger language models (do Carmo
& Moorkens, 2022), often neglecting the needs of users of such
technology (Birhane et al., 2022).
According to Shneiderman (2022), the goal of technology development
has been the creation of an intelligent agent that emulates human
behaviour to increase automation. As a response, a novel technology
design framework has gained a foothold recently: human-centered AI
(HCAI), where instead of human emulation, the aim is to produce a
powerful tool that augments human capabilities, enhances performance,
and empowers users, who are at all instances in supervisory control of
such systems (Shneiderman 2022). A key element in the HCAI framework
is that of “augmentation”. Human performance is constrained by
cognitive load and augmentation seeks to overcome this limitation and
to amplify, rather than replace, human intelligence. This shift,
moving from emulation to empowerment, places humans at the centre of
AI/language technology (Raisamo et al., 2019) instead of just “in the
loop”. This reorientation, emphasizing the synergy and collaboration
between humans and machines, presages a new era where technology
becomes a partner rather than a substitute. In translation and
interpreting, this human-centered, augmented approach has been
recently suggested (O’Brien, 2023). When applied to machine
translation (MT), we can talk about human-centered, augmented MT
(HCAMT) (Briva-Iglesias, 2024). Early studies on HCAMT show that,
through the analysis of machine translation user experience (MTUX),
there are human-MT interactions that augment users, allowing them to
be more comfortable with technology, and more in control, while
enhancing their performance (Briva-Iglesias et al., 2023).
The successful implementation of HCAMT for translation and
interpreting may lead to sustainable, diverse, and ethically sound
development and utilisation of MT systems and other technological
tools through a wide variety of users and use-cases. Consequently,
this special issue calls for proposals that aim to trigger a step
change in the point of view from which MT and language technologies
are developed and adopted by translators, interpreters and other MT
users, and invites proposals that include, but are not limited to:
New methodologies for measuring HCAMT experience, fostering tools,
workflows and systems in translation, interpreting, and other
use-cases.
Research on the MTUX of people interacting with MT systems, aiming to
identify factors that contribute to effective human-machine
collaboration and human empowerment, rather than emulation.
Examining how HCAMT can serve a wide variety of users and use-cases,
empowering their communication needs, augmenting their abilities,
while also promoting diversity and inclusion in language technology
applications.
Discussion on ethical issues in the development and application of
HCAMT, including privacy, bias, inclusivity, and trust.
Design and evaluation of systems that facilitate effective
collaboration between translators/interpreters and MT technologies.
Submissions are expected to go beyond consideration of user
interaction with MT to really engage with the topic of augmentation
and empowerment.
Submission Guidelines:
Submissions should adhere to the journal's formatting guidelines. All
manuscripts will undergo a rigorous peer-review process to ensure the
highest quality and relevance. Please submit abstracts of at least 500
words and no more than 1000 words in English, including relevant
references (not included in the word count), to both Vicent
Briva-Iglesias (vicent.brivaiglesias at dcu.ie) and Sharon O’Brien
(sharon.obrien at dcu.ie) in the same email, before 1 May 2025.
Important Dates:
Submission of proposals (abstract) for papers: 1 May 2025
Acceptance of the submitted abstract: 1 July 2025.
Submission of papers: 1 December 2025 (around 8,000 words, including
references, notes and spaces).
Notification of Acceptance: March 2026
Submission of the final versions of the papers: 1 June 2026.
Publication: December 2026.
Announcement:
https://lans-tts.uantwerpen.be/index.php/LANS-TTS/announcement/view/26
Contact Information:
For inquiries about the special issue, please contact the guest
editors:
Vicent Briva-Iglesias (vicent.brivaiglesias at dcu.ie)
Sharon O’Brien (sharon.obrien at dcu.ie)
We look forward to receiving your submissions and advancing the
discourse on human-centered, augmented machine translation together.

Linguistic Field(s): Applied Linguistics
                     Cognitive Science
                     Computational Linguistics
                     Translation

Subject Language(s): English (eng)

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