Research Focus: Human-Machine Symbiosis

-Better synergy and collaboration between human translators and machine translation tools.

-Meaningful human control over machine translation tools (e.g. closed loop feedback to re-shape)

-Adaptation and personalization of machine translation tools

-Assistance tools to support (subjective) human skills

-Human-machine co-learning

Machine Translation Summit 2019 Publication

1st International Conference on Artificial Intelligence in HCI (AI-HCI), Part of HCI 2020 Publication

Defining a Human-Machine Teaming Model for AI-powered Human-centered Machine Translation Agent by Learning from Human-Human Group Discussion: Dialog Categories and Dialog Moves

Human versus Machine and Human-Machine Teaming on Masked Language Modeling Tasks

KLSI Methods for Human Simultaneous Interpretation and Towards Building a Simultaneous Machine Translation System Reflecting the KLSI Methods

Assisting Text Localization and Transcreation Tasks Using AI-based Masked Language Modeling

Morality Beyond the Lines: Detecting Moral Sentiment using AI-generated Synthetic Context