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Context-Dependent Dictionary for Translators
Fanta, Petr ; Bojar, Ondřej (advisor) ; Kuboň, Vladislav (referee)
During a manual translation of short texts, such as texts occurring on social networks or microblogs (e.g., Twitter), translators are often forced to gather additional information from various sources. These can include less common words, domain-specific terms, or numerous abbreviations. The aim of this thesis is to design and implement a system which automatically creates a minimal context-dependent dictionary for the given short message. The system identifies suitable dictionary entries in the translated text and searches for their definitions, translations, and examples from available open sources, or extracts them automatically from a parallel corpus. The resulted dictionary is ideally sufficient for human translators to understand the message, and to choose appropriate translation equivalent (including technical terms). An empirical evaluation is based on statistics which tracks how often users were satisfied with the proposed entries, how often the entries were incorrect and to what extent the system correctly identified the relevance for the input text.
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