Platvorm neuromasintõlke süsteemide demonstreerimiseks ning kasutaja andmete kogumiseks
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2017
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Käesolev magistritöö keskendub probleemile, et ei ole olemas avaliku lähtekoodiga masintõlke platvormi, mis lubaks ka andmete kogumist lõpp-kasutajatelt. Sellise süsteemi olemasolu lihtsustaks hüpoteeside testimist ning eksperimentide läbiviimist nii gruppide kui ka individuaalsete uurijate poolt masintõlke valdkonnas. Lisaks sellele, saaks koguda ka tagasisidet lõppkasutajatelt. Töö autor arendas platvormi, valideeris ning täiustas seda pidevalt läbi kasutajate tagasiside. Autor on mõelnud ka platvormi arhitektuurilise disaini peale, kasutades tarkvaraarenduse parimaid tavasid. Selle tulemusena on olemas avatud lähtekoodiga platvorm masintõlke süsteemidele, mis võimaldab ka andmete kogumist.
The central problem this work focuses on is that there are no open-source platforms for machine translation systems, which also allow collecting data from end-users.The existence of such a system will greatly simplify the testing of hypotheses and the conduction experiments both by groups and individual researchers in the field of machine translation as well a receiving feedback from endusers.The author creates a platform from scratch, validates and continually improves its performance based on feedback from users. The author also thinks of the architecture design of the platform based on the best software engineering practices.As a result, there is now an open-source platform for machine translation systems, which also allows collecting data from users.
The central problem this work focuses on is that there are no open-source platforms for machine translation systems, which also allow collecting data from end-users.The existence of such a system will greatly simplify the testing of hypotheses and the conduction experiments both by groups and individual researchers in the field of machine translation as well a receiving feedback from endusers.The author creates a platform from scratch, validates and continually improves its performance based on feedback from users. The author also thinks of the architecture design of the platform based on the best software engineering practices.As a result, there is now an open-source platform for machine translation systems, which also allows collecting data from users.