MT Evaluation in the Context of Language Complexity
The paper focuses on investigating the impact of artificial agent (machine translator) on human agent (posteditor) using a proposed methodology, which is based on language complexity measures, POS tags, frequent tagsets, association rules, and their summarization. We examine this impact from the poi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/2806108 |
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| _version_ | 1832561270165864448 |
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| author | Dasa Munkova Michal Munk null Ľubomír Benko Jiri Stastny |
| author_facet | Dasa Munkova Michal Munk null Ľubomír Benko Jiri Stastny |
| author_sort | Dasa Munkova |
| collection | DOAJ |
| description | The paper focuses on investigating the impact of artificial agent (machine translator) on human agent (posteditor) using a proposed methodology, which is based on language complexity measures, POS tags, frequent tagsets, association rules, and their summarization. We examine this impact from the point of view of language complexity in terms of word and sentence structure. By the proposed methodology, we analyzed 24 733 tags of English to Slovak translations of technical texts, corresponding to the output of two MT systems (Google Translate and the European Commission’s MT tool). We used both manual (adequacy and fluency) and semiautomatic (HTER metric) MT evaluation measures as the criteria for validity. We show that the proposed methodology is valid based on the evaluation of frequent tagsets and rules of MT outputs produced by Google Translate or of the European Commission’s MT tool, and both postedited MT (PEMT) outputs using baseline methods. Our results have also shown that PEMT output produced by Google Translate is characterized by more frequent tagsets such as verbs in the infinitive with modal verbs compared to its MT output, which is characterized by masculine, inanimate nouns in locative of singular. In the MT output, produced by the European Commission’s MT tool, the most frequent tagset was verbs in the infinitive compared to its postedited MT output, where verbs in imperative and the second person of plural occurred. These findings are also obtained from the use of the proposed methodology for MT evaluation. The contribution of the proposed methodology is an identification of systematic not random errors. Additionally, the study can also serve as information for optimizing the translation process using postediting. |
| format | Article |
| id | doaj-art-2025cab96cff42f19361dbebc7f06d46 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-2025cab96cff42f19361dbebc7f06d462025-02-03T01:25:21ZengWileyComplexity1099-05262021-01-01202110.1155/2021/2806108MT Evaluation in the Context of Language ComplexityDasa Munkova0Michal Munk1null Ľubomír Benko2Jiri Stastny3Department of Computer ScienceDepartment of Computer ScienceDepartment of Computer ScienceInstitute of Automation and Computer ScienceThe paper focuses on investigating the impact of artificial agent (machine translator) on human agent (posteditor) using a proposed methodology, which is based on language complexity measures, POS tags, frequent tagsets, association rules, and their summarization. We examine this impact from the point of view of language complexity in terms of word and sentence structure. By the proposed methodology, we analyzed 24 733 tags of English to Slovak translations of technical texts, corresponding to the output of two MT systems (Google Translate and the European Commission’s MT tool). We used both manual (adequacy and fluency) and semiautomatic (HTER metric) MT evaluation measures as the criteria for validity. We show that the proposed methodology is valid based on the evaluation of frequent tagsets and rules of MT outputs produced by Google Translate or of the European Commission’s MT tool, and both postedited MT (PEMT) outputs using baseline methods. Our results have also shown that PEMT output produced by Google Translate is characterized by more frequent tagsets such as verbs in the infinitive with modal verbs compared to its MT output, which is characterized by masculine, inanimate nouns in locative of singular. In the MT output, produced by the European Commission’s MT tool, the most frequent tagset was verbs in the infinitive compared to its postedited MT output, where verbs in imperative and the second person of plural occurred. These findings are also obtained from the use of the proposed methodology for MT evaluation. The contribution of the proposed methodology is an identification of systematic not random errors. Additionally, the study can also serve as information for optimizing the translation process using postediting.http://dx.doi.org/10.1155/2021/2806108 |
| spellingShingle | Dasa Munkova Michal Munk null Ľubomír Benko Jiri Stastny MT Evaluation in the Context of Language Complexity Complexity |
| title | MT Evaluation in the Context of Language Complexity |
| title_full | MT Evaluation in the Context of Language Complexity |
| title_fullStr | MT Evaluation in the Context of Language Complexity |
| title_full_unstemmed | MT Evaluation in the Context of Language Complexity |
| title_short | MT Evaluation in the Context of Language Complexity |
| title_sort | mt evaluation in the context of language complexity |
| url | http://dx.doi.org/10.1155/2021/2806108 |
| work_keys_str_mv | AT dasamunkova mtevaluationinthecontextoflanguagecomplexity AT michalmunk mtevaluationinthecontextoflanguagecomplexity AT nulllubomirbenko mtevaluationinthecontextoflanguagecomplexity AT jiristastny mtevaluationinthecontextoflanguagecomplexity |