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Title:Analiza metrik za avtomatsko vrednotenje strojnih prevodov
Authors:Arzenšek, Klemen (Author)
Sepesy Maučec, Mirjam (Mentor) More about this mentor... New window
Donaj, Gregor (Co-mentor)
Files:.pdf UN_Arzensek_Klemen_2018.pdf (1,18 MB)
MD5: F9825EF7DEDD0FF7B25C53DA6EE62D70
 
.zip UN_Arzensek_Klemen_2018.zip (1,12 MB)
MD5: 369923BCB8A8FCD01DAC0D05222CB66D
 
Language:Slovenian
Work type:Diploma project paper (mb13)
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V projektu smo opravili pregled metrik za avtomatsko vrednotenje strojnih prevodov. Testirali smo določene metrike za ocenjevanje prevodov iz angleščine v slovenščino. Vsi testi so bili opravljeni z metrikami direktno iz Linux terminala. Testirali smo tako, da smo vsako metriko oz. sklop metrik lokalno zaganjali, vsako metriko posebej z več testnimi vzorci, da smo dobili več rezultatov in tako odpravili nepotrebna odstopanja. V poročilu bomo predstavili tudi osnove strojnega prevajanja in osnove vrednotenja le-tega. Metrike, ki smo jih uporabili pri testiranju, bomo podrobno opisali in v praksi preizkusili.
Keywords:strojno prevajanje, evalvacija, metrika avtomatske evalvacije
Year of publishing:2018
Publisher:[K. Arzenšek]
Source:Maribor
UDC:621.39
COBISS_ID:22109462 New window
NUK URN:URN:SI:UM:DK:IGBLBHYE
Views:596
Downloads:52
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:18.09.2018

Secondary language

Language:English
Title:Analysis of metrics for automatic evaluation of machine translation
Abstract:In the project, we made an overview of automatic metrics for machine translation evaluation. We tested the quality of translations from English into Slovene. All the tests were performed with metrics directly from the Linux terminal. We tested the metric locally. Each metric was tested separately with several test samples to obtain results without unnecessary deviations. The report will first present the basics of machine translation and the basics of evaluation. The metrics we have used in the testing will be described in detail and practically tested to see how they work.
Keywords:machine translation, evaluation, automated evaluation metric


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