Machine Translation and Human Interaction
Scientic Supervisor / Contact Person
Name and Surname
Celia Rico
ORCID (link)
Localization & Research Area
Faculty / Institute
Faculty of Language Studies
Department
Estudios Románicos, Franceses, Italianos y Traducción
Research Area
Social Sciences and Humanities (SOC)
MSCA & ERC experience
Research group / research team hosted any MSCA fellow?
No
Research group / research team have any ERC beneficiaries?
No
Research Team & Research Topic
Website of the Research team / Research Group / Department
Brief description of the Research Team / Research Group / Department
Machine translation is a research field that intersects multiple disciplines, including computer science, computational linguistics, mathematics, translation studies, and, more recently, artificial intelligence. With recent technological developments, there has been growing interest from translation studies in machine translation—an area that, precisely due to its interdisciplinary nature, requires the application of a dedicated research methodology, including specific tools and datasets.
The interaction between machine translation and human translators is a key aspect of this field. While machine translation systems have significantly improved in accuracy and fluency, human expertise remains essential, ensuring contextual accuracy, and handling complex linguistic nuances. This collaboration between humans and AI leads to more efficient workflows, enhancing productivity while maintaining high-quality translations.
The interaction between machine translation and human translators is a key aspect of this field. While machine translation systems have significantly improved in accuracy and fluency, human expertise remains essential, ensuring contextual accuracy, and handling complex linguistic nuances. This collaboration between humans and AI leads to more efficient workflows, enhancing productivity while maintaining high-quality translations.
Research lines / projects proposed
1. Quality and Evaluation
Development of more reliable automatic evaluation metrics for MT output.
Comparative analysis of human and machine translations in specific language pairs.
The impact of post-editing on translation quality and efficiency.
2. Human-Machine Interaction
Cognitive processes involved in post-editing machine translations.
The role of human translators in improving neural machine translation (NMT) systems.
User experience and ergonomics in computer-assisted translation (CAT) tools with MT integration.
3. Ethics and Bias in Machine Translation
Bias detection and mitigation in MT models (e.g., gender, cultural biases).
Ethical implications of replacing human translators with AI.
Data privacy concerns in cloud-based MT services.
4. Multimodal and Context-Aware MT
Incorporating contextual information to improve MT accuracy.
The role of visual and audio cues in improving MT for subtitling and dubbing.
Speech-to-text MT applications for real-time communication.
5.Epistemic Capacities of MT Users
Assessment of the cognitive and strategic skills required for effective interaction with MT.
Impact of linguistic and translation knowledge on post-editing quality.
Training and development of critical competencies for interpreting and correcting machine translations.
Development of more reliable automatic evaluation metrics for MT output.
Comparative analysis of human and machine translations in specific language pairs.
The impact of post-editing on translation quality and efficiency.
2. Human-Machine Interaction
Cognitive processes involved in post-editing machine translations.
The role of human translators in improving neural machine translation (NMT) systems.
User experience and ergonomics in computer-assisted translation (CAT) tools with MT integration.
3. Ethics and Bias in Machine Translation
Bias detection and mitigation in MT models (e.g., gender, cultural biases).
Ethical implications of replacing human translators with AI.
Data privacy concerns in cloud-based MT services.
4. Multimodal and Context-Aware MT
Incorporating contextual information to improve MT accuracy.
The role of visual and audio cues in improving MT for subtitling and dubbing.
Speech-to-text MT applications for real-time communication.
5.Epistemic Capacities of MT Users
Assessment of the cognitive and strategic skills required for effective interaction with MT.
Impact of linguistic and translation knowledge on post-editing quality.
Training and development of critical competencies for interpreting and correcting machine translations.
Key words
Application requirements
Professional Experience & Documents
The interested fellows must submit the following documents:
Curriculum Vitae
Letter of motivation
Research interests
A description of soft skills
Curriculum Vitae
Letter of motivation
Research interests
A description of soft skills
One Page Proposal
You can attach the 'One Page Proposal' to enhance the attractiveness of your application. Supervisors usually appreciate it. Please take into account your background and the information provided in Research Team & Research Topic section to fill in it.
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