NMT verb rendering: A cognitive approach to informing Arabic-into-English post-editing
Machine translation (MT) has made significant strides and has reached accuracy levels that often make the post-editing (PE) of MT output a viable alternative to manual translation. However, despite professional translators increasingly considering PE as a valid stage in their translation workflow, l...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2022-07-01
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| Series: | Open Linguistics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/opli-2022-0192 |
| _version_ | 1828203017533390848 |
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| author | Almanna Ali Jamoussi Rafik |
| author_facet | Almanna Ali Jamoussi Rafik |
| author_sort | Almanna Ali |
| collection | DOAJ |
| description | Machine translation (MT) has made significant strides and has reached accuracy levels that often make the post-editing (PE) of MT output a viable alternative to manual translation. However, despite professional translators increasingly considering PE as a valid stage in their translation workflow, little has been done to investigate MT output for the purpose of informing training in PE. Against this background, the present project focuses on the handling of tense and aspect configurations in the English translation of Arabic sentences using current neural machine translation (NMT) systems. Using a dataset of representative Arabic sentences, the output of five NMT engines was assessed against reference translations. The investigation reveals regressing accuracy levels when comparing morphological, structural, and contextual tenses. These findings are believed to represent valuable information that contributes to a more informed training in the PE of Arabic-into-English NMT output. |
| first_indexed | 2024-04-12T11:58:22Z |
| format | Article |
| id | doaj.art-92140f3b706846bf9f2c9d8e349cf498 |
| institution | Directory Open Access Journal |
| issn | 2300-9969 |
| language | English |
| last_indexed | 2024-04-12T11:58:22Z |
| publishDate | 2022-07-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Linguistics |
| spelling | doaj.art-92140f3b706846bf9f2c9d8e349cf4982022-12-22T03:33:57ZengDe GruyterOpen Linguistics2300-99692022-07-018131032710.1515/opli-2022-0192NMT verb rendering: A cognitive approach to informing Arabic-into-English post-editingAlmanna Ali0Jamoussi Rafik1Translation and Interpreting Studies Department, Hamad Bin Khalifa University, Al-Gharafa, Doha, 945, QatarFaculty of Language Studies, Sohar University, Sohar, OmanMachine translation (MT) has made significant strides and has reached accuracy levels that often make the post-editing (PE) of MT output a viable alternative to manual translation. However, despite professional translators increasingly considering PE as a valid stage in their translation workflow, little has been done to investigate MT output for the purpose of informing training in PE. Against this background, the present project focuses on the handling of tense and aspect configurations in the English translation of Arabic sentences using current neural machine translation (NMT) systems. Using a dataset of representative Arabic sentences, the output of five NMT engines was assessed against reference translations. The investigation reveals regressing accuracy levels when comparing morphological, structural, and contextual tenses. These findings are believed to represent valuable information that contributes to a more informed training in the PE of Arabic-into-English NMT output.https://doi.org/10.1515/opli-2022-0192aspectarabic-english translationcognitive linguisticscontextual tensemorphological tenseneural machine translationstructural tensepost-editing |
| spellingShingle | Almanna Ali Jamoussi Rafik NMT verb rendering: A cognitive approach to informing Arabic-into-English post-editing Open Linguistics aspect arabic-english translation cognitive linguistics contextual tense morphological tense neural machine translation structural tense post-editing |
| title | NMT verb rendering: A cognitive approach to informing Arabic-into-English post-editing |
| title_full | NMT verb rendering: A cognitive approach to informing Arabic-into-English post-editing |
| title_fullStr | NMT verb rendering: A cognitive approach to informing Arabic-into-English post-editing |
| title_full_unstemmed | NMT verb rendering: A cognitive approach to informing Arabic-into-English post-editing |
| title_short | NMT verb rendering: A cognitive approach to informing Arabic-into-English post-editing |
| title_sort | nmt verb rendering a cognitive approach to informing arabic into english post editing |
| topic | aspect arabic-english translation cognitive linguistics contextual tense morphological tense neural machine translation structural tense post-editing |
| url | https://doi.org/10.1515/opli-2022-0192 |
| work_keys_str_mv | AT almannaali nmtverbrenderingacognitiveapproachtoinformingarabicintoenglishpostediting AT jamoussirafik nmtverbrenderingacognitiveapproachtoinformingarabicintoenglishpostediting |