NMT’s wonderland where people turn into rabbits : a study on the comprehensibility of newly invented words in NMT output
- Author
- Lieve Macken (UGent) , Laura Van Brussel and Joke Daems (UGent)
- Organization
- Abstract
- Machine translation (MT) quality has improved enormously since the arrival of neural machine translation (NMT). The most noticeable improvement compared to statistical MT systems is the increased grammaticality and fluency of the produced MT output. At the lexical level, the quality of NMT systems is less promising. New types of lexical mistakes appear in NMT output, such as the occurrence of non existing words, i.e. words that are not part of the vocabulary of the target language and were thus invented by the NMT system. For MT use cases in which readers only have access to the MT output without the source text, such non-existing words can affect comprehension as the intended source meaning may not be recovered. To investigate if and to what extent non-existing words in English-to-Dutch NMT output impair comprehension, an experiment was set up in SurveyMonkey. Eighty-six participants were given 15 non-existing words (5 single words and 10 noun compounds) and were either asked to describe the meaning of these words or to select the correct meaning from a predefined list. The words were presented either in isolation or in sentence context. Participants were asked to indicate how confident they were about their answer. Results show that non existing words indeed impair comprehension as in 60% of the cases the participants gave a wrong answer. Sentence context had a positive impact and made it easier for the participants to determine the meaning of the non-existing word. Participants were also more confident about their answer when the words were presented in sentence context.
- Keywords
- LT3
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8639616
- MLA
- Macken, Lieve, et al. “NMT’s Wonderland Where People Turn into Rabbits : A Study on the Comprehensibility of Newly Invented Words in NMT Output.” COMPUTATIONAL LINGUISTICS IN THE NETHERLANDS JOURNAL, vol. 9, 2019, pp. 67–80.
- APA
- Macken, L., Van Brussel, L., & Daems, J. (2019). NMT’s wonderland where people turn into rabbits : a study on the comprehensibility of newly invented words in NMT output. COMPUTATIONAL LINGUISTICS IN THE NETHERLANDS JOURNAL, 9, 67–80.
- Chicago author-date
- Macken, Lieve, Laura Van Brussel, and Joke Daems. 2019. “NMT’s Wonderland Where People Turn into Rabbits : A Study on the Comprehensibility of Newly Invented Words in NMT Output.” COMPUTATIONAL LINGUISTICS IN THE NETHERLANDS JOURNAL 9: 67–80.
- Chicago author-date (all authors)
- Macken, Lieve, Laura Van Brussel, and Joke Daems. 2019. “NMT’s Wonderland Where People Turn into Rabbits : A Study on the Comprehensibility of Newly Invented Words in NMT Output.” COMPUTATIONAL LINGUISTICS IN THE NETHERLANDS JOURNAL 9: 67–80.
- Vancouver
- 1.Macken L, Van Brussel L, Daems J. NMT’s wonderland where people turn into rabbits : a study on the comprehensibility of newly invented words in NMT output. COMPUTATIONAL LINGUISTICS IN THE NETHERLANDS JOURNAL. 2019;9:67–80.
- IEEE
- [1]L. Macken, L. Van Brussel, and J. Daems, “NMT’s wonderland where people turn into rabbits : a study on the comprehensibility of newly invented words in NMT output,” COMPUTATIONAL LINGUISTICS IN THE NETHERLANDS JOURNAL, vol. 9, pp. 67–80, 2019.
@article{8639616,
abstract = {{Machine translation (MT) quality has improved enormously since the arrival of neural machine translation (NMT). The most noticeable improvement compared to statistical MT systems is the increased grammaticality and fluency of the produced MT output. At the lexical level, the quality of NMT systems is less promising. New types of lexical mistakes appear in NMT output, such as the occurrence of non existing words, i.e. words that are not part of the vocabulary of the target language and were thus invented by the NMT system. For MT use cases in which readers only have access to the MT output without the source text, such non-existing words can affect comprehension as the intended source meaning may not be recovered. To investigate if and to what extent non-existing words in English-to-Dutch NMT output impair comprehension, an experiment was set up in SurveyMonkey. Eighty-six participants were given 15 non-existing words (5 single words and 10 noun compounds) and were either asked to describe the meaning of these words or to select the correct meaning from a predefined list. The words were presented either in isolation or in sentence context. Participants were asked to indicate how confident they were about their answer. Results show that non existing words indeed impair comprehension as in 60% of the cases the participants gave a wrong answer. Sentence context had a positive impact and made it easier for the participants to determine the meaning of the non-existing word. Participants were also more confident about their answer when the words were presented in sentence context.}},
author = {{Macken, Lieve and Van Brussel, Laura and Daems, Joke}},
issn = {{2211-4009}},
journal = {{COMPUTATIONAL LINGUISTICS IN THE NETHERLANDS JOURNAL}},
keywords = {{LT3}},
language = {{eng}},
pages = {{67--80}},
title = {{NMT’s wonderland where people turn into rabbits : a study on the comprehensibility of newly invented words in NMT output}},
url = {{https://www.clinjournal.org/clinj/article/view/93}},
volume = {{9}},
year = {{2019}},
}