Assessing complexity and difficulty levels of machine-translated texts

Fonseca, Norma Barbosa de Lima; Alves, Fábio

doi:10.14393/ll63-v32n1a2016-16

L&L

2016

DOI: 10.14393/ll63-v32n1a2016-16

|View full text |Cite

Assessing complexity and difficulty levels of machine-translated texts

Norma Barbosa de Lima Fonseca

Fábio Alves²

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2019

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

MT error detection and correction by Chinese language learners

Zhang,

Osborne,

Moorkens

2024

TIS

View full text Add to dashboard Cite

This article analyzes texts that have been generated by machine translation (MT) and post-edited by native English-speaking trainee translators (English>Chinese) who are also Chinese language learners enrolled in a four-year undergraduate translation program. The project examines the work product of trainee translators to categorize 122 errors that are (un)noticed and (un)corrected by them. MT errors in the Accuracy category were best identified and corrected, followed by those in the Lexicon and Fluency categories. Trainee translators who were advanced language learners outperformed the intermediate group in MT error detection and correction, especially in the Lexicon category. This study sheds light upon the use of raw MT output as meaningful input for trainee translators who are in the process of learning Chinese. Its findings provide information regarding the type of exercises needed in language learning and translation training for students with different levels of language proficiency.

show abstract

MT error detection and correction by Chinese language learners

Zhang,

Osborne,

Moorkens

2024

TIS

View full text Add to dashboard Cite

show abstract

Analysing the impact of TAPs on temporal, technical and cognitive effort in monolingual post-editing

Fonseca

2019

Perspectives

View full text Add to dashboard Cite

Machine Translation: Teaching and Learning Issues

Esqueda

2021

Trab. linguist. apl.

View full text Add to dashboard Cite

Considering the boost in technological development, and that machine translation has been widely used by both industry and academia, the main goal of this paper is to describe possibilities for the incorporation of a basic machine translation module in a Translation program at university level. The didactic proposal herein presented aims at providing Translation students ways of identifying general output results different modern machine translation systems have in common. Through a task-based teaching approach, students may assess machine translation strengths and weaknesses in order to make better use of this technology.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Assessing complexity and difficulty levels of machine-translated texts

Cited by 3 publications

References 15 publications

MT error detection and correction by Chinese language learners

MT error detection and correction by Chinese language learners

Analysing the impact of TAPs on temporal, technical and cognitive effort in monolingual post-editing

Machine Translation: Teaching and Learning Issues

Contact Info

Product

Resources

About