Lucas Nunes Vieira
Biographic Data
| ID | 6546144 |
|---|---|
| NAME | Lucas Nunes Vieira |
| GIVEN NAMES | Lucas Nunes |
| FAMILY NAME | Vieira |
| SIGNATURE | VIEIRA L N |
| AFFILIATIONS | University of Bristol |
| ORCID | 0000-0003-3038-4001 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Translators’ perceptions of privacy, confidentiality and information security
As translators increasingly work in Artificial Intelligence (AI)-powered cloud-based environments, privacy and confidentiality risks affecting translation resources and their users are likely to increase. This study explores translators’ data management practices and their perceptions of privacy, confidentiality and information security. Drawing on a survey of 439 professional translators, three key concerns emerged. Firstly, translators generall…
Privacy and everyday users of machine translation
The concept of privacy is central to technology use, but in machine translation (MT) research the meaning of privacy, and what it represents to everyday MT users, are both often left unquestioned. This article examines user conceptualisations of privacy and their implications for the understanding of human-MT interaction. It draws on the privacy literature, on an online forum and on a survey of MT users. The findings show that while users have co…
What has changed with neural machine translation? A critical review of human factors
In recent years, the push towards automation and translation productivity led to great efforts dedicated to the development of machine translation (MT) systems. Neural machine translation (NMT) represents the latest of these efforts. In this paper we present a critical review of human factors in NMT research with two goals: to provide a snapshot of research in NMT involving human stakeholders, and to appraise how professional translators have bee…
Understanding the societal impacts of machine translation
The ready availability of machine translation (MT) systems such as Google Translate has profoundly changed how society engages with multilingual communication practices. In addition to private use situations, this technology is now used to overcome language barriers in high-risk settings such as hospitals and courts. MT errors pose serious risks in environments like these, but there is little understanding of the nature of these risks and of the …
Machine translation in the news
Machine translation (MT) is now firmly in the public eye. The media can reflect and influence the public perception of MT and, by extension, of translation itself, but the news coverage of MT has to date remained largely unexplored. This study draws on the news framing literature to present an analysis of how MT is described in the written press. Based on a sample of 284 MT-focused newspaper articles, the news reporting on MT was found to be sign…
Translating perceptions and managing expectations
The use of machine translation (MT) in professional translation tasks can change not only how translators work, but also how projects are managed and the expectations they entail across translation supply chains. Previous research has looked extensively into translators’ attitudes to MT but has often ignored important aspects of how translators’ views interact with those of other language industry stakeholders. This article presents a contrastive…
Cognitive effort and different task foci in post-editing of machine translation
Post-editing of machine translation is gaining popularity as a solution to the ever-increasing demands placed on human translators. There has been a great deal of research in this area aimed at determining the feasibility of post-editing and at predicting post-editing effort based on source-text features and machine translation errors. However, considerably less is known about the mental workings of post-editing and post-editors’ decision-making …
No prominent works on this page.
Cognitive effort and different task foci in post-editing of machine translation
Post-editing of machine translation is gaining popularity as a solution to the ever-increasing demands placed on human translators. There has been a great deal of research in this area aimed at determining the feasibility of post-editing and at predicting post-editing effort based on source-text features and machine translation errors. However, considerably less is known about the mental workings of post-editing and post-editors’ decision-making …
Translating perceptions and managing expectations
The use of machine translation (MT) in professional translation tasks can change not only how translators work, but also how projects are managed and the expectations they entail across translation supply chains. Previous research has looked extensively into translators’ attitudes to MT but has often ignored important aspects of how translators’ views interact with those of other language industry stakeholders. This article presents a contrastive…
Machine translation in the news
Machine translation (MT) is now firmly in the public eye. The media can reflect and influence the public perception of MT and, by extension, of translation itself, but the news coverage of MT has to date remained largely unexplored. This study draws on the news framing literature to present an analysis of how MT is described in the written press. Based on a sample of 284 MT-focused newspaper articles, the news reporting on MT was found to be sign…
Understanding the societal impacts of machine translation
The ready availability of machine translation (MT) systems such as Google Translate has profoundly changed how society engages with multilingual communication practices. In addition to private use situations, this technology is now used to overcome language barriers in high-risk settings such as hospitals and courts. MT errors pose serious risks in environments like these, but there is little understanding of the nature of these risks and of the …
What has changed with neural machine translation? A critical review of human factors
In recent years, the push towards automation and translation productivity led to great efforts dedicated to the development of machine translation (MT) systems. Neural machine translation (NMT) represents the latest of these efforts. In this paper we present a critical review of human factors in NMT research with two goals: to provide a snapshot of research in NMT involving human stakeholders, and to appraise how professional translators have bee…
Privacy and everyday users of machine translation
The concept of privacy is central to technology use, but in machine translation (MT) research the meaning of privacy, and what it represents to everyday MT users, are both often left unquestioned. This article examines user conceptualisations of privacy and their implications for the understanding of human-MT interaction. It draws on the privacy literature, on an online forum and on a survey of MT users. The findings show that while users have co…
Translators’ perceptions of privacy, confidentiality and information security
As translators increasingly work in Artificial Intelligence (AI)-powered cloud-based environments, privacy and confidentiality risks affecting translation resources and their users are likely to increase. This study explores translators’ data management practices and their perceptions of privacy, confidentiality and information security. Drawing on a survey of 439 professional translators, three key concerns emerged. Firstly, translators generall…
Computer Science (5 works) · Interpreting and Communication in Healthcare (4 works) · Natural Language Processing Techniques (4 works) · Psychology (4 works) · Translation Studies and Practices (4 works) · Artificial Intelligence (3 works) · Engineering (3 works) · Knowledge management (3 works) · Perception (3 works) · Political science (3 works)