paper-with-me

홈 › Papers

The impact of translation competence on error recognition of neural MT

2022-09-01 · AMTA 2022 9 · Moritz J Schaeffer

Schaeffer et al. (2019) studied whether translation student’s error recognition processes dif- fered from those in professional translators. The stimuli consisted of complete texts, which contained errors of five kinds, following Mertin’s (2006) error typology. Translation students and professionals saw translations which contained errors produced by human translators and which had to be revised. Vardaro et al (2019) followed the same logic, but first determined the frequency of error types produced by the EU commission’s NMT system and then pre- sented single sentences containing errors based on the MQM typology. Participants in Vardaro et al (2019) were professional translators employed by the EU. For the current pur- pose, we present the results from a comparison between those 30 professionals in Vardaro et al (2019) and a group of 30 translation students. We presented the same materials as in Vardaro et al (2019) and tracked participants’ eye movements and keystrokes. Results show that translation competence interacts with how errors are recognized and corrected during post-editing. We discuss the results of this study in relation to current models of the transla- tion process by contrasting the predictions these make with the evidence from our study

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

NMTTranslation

Similar Papers 제목 키워드 기반

Post-Editing Job Profiles for Subtitlers

2021-08-01 · MTSummit 2021 8 · Anke Tardel, Silvia Hansen-Schirra, Jean Nitzke

Language technologies, such as machine translation (MT), but also the application of artificial intelligence in general and an abundance of CAT tools and platforms have an increasing influence on the translation market. …

Machine TranslationTranslation

How Annotation Trains Annotators: Competence Development in Social Influence Recognition

2026-04-03 · Maciej Markiewicz, Beata Bajcar, Wiktoria Mieleszczenko-Kowszewicz, Aleksander Szczęsny 외 arxiv

Human data annotation, especially when involving experts, is often treated as an objective reference. However, many annotation tasks are inherently subjective, and annotators' judgments may evolve over time. This study i…

Competence-based Curriculum Learning for Multilingual Machine Translation

2021-09-09 · Findings (EMNLP) 2021 11 · Mingliang Zhang, Fandong Meng, Yunhai Tong, Jie zhou

Currently, multilingual machine translation is receiving more and more attention since it brings better performance for low resource languages (LRLs) and saves more space. However, existing multilingual machine translati…

Machine TranslationTranslation

Phonetically-Oriented Word Error Alignment for Speech Recognition Error Analysis in Speech Translation

2019-04-24 · Nicholas Ruiz, Marcello Federico

We propose a variation to the commonly used Word Error Rate (WER) metric for speech recognition evaluation which incorporates the alignment of phonemes, in the absence of time boundary information. After computing the Le…

speech-recognitionSpeech RecognitionTranslationWord Alignment

Sentence Boundary Augmentation For Neural Machine Translation Robustness

2020-10-21 · Daniel Li, Te I, Naveen Arivazhagan, Colin Cherry 외

Neural Machine Translation (NMT) models have demonstrated strong state of the art performance on translation tasks where well-formed training and evaluation data are provided, but they remain sensitive to inputs that inc…

Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Data AugmentationMachine Translation+6