Ορθή Επανάληψη: Διάλεξη με θέμα: "Recent Developments in Language Technology"

 

Το Τμήμα Πληροφορικής του Ιονίου Πανεπιστημίου σας προσκαλεί στη διάλεξη της κας Κορδόνη Ευαγγελίας, Καθηγήτρια Υπολογιστικής Γλωσσολογίας στο Πανεπιστήμιο Humboldt του Βερολίνου, που θα πραγματοποιηθεί την Τετάρτη 16/10, ώρα 17:00 στο αμφιθέατρο 2, κτίριο Ιστορίας με θέμα :

"Recent Developments in Language Technology"

Abstract:

This talk focuses on recent developments in Language Technology (LT) applications, specifically, Machine Translation (MT).

Machine Translation (MT) has evolved along with different types of computer-assisted translation tools and a notable progress has been achieved in improving the quality of translations. However, in spite of the recent positive developments in translation technologies, not all problems have been solved and in particular the identification, interpretation and translation of Multiword Expressions (MWEs) still represent open challenges, both from a theoretical and a practical point of view. The low standard of analysis and translation of MWEs in translation technologies suggest that there is the need to invest in further research with the goal of improving the performance of the various translation applications. Here I will describe a concrete evaluation of the significance of phrasal verb treatment for obtaining better quality statistical machine translation (SMT) results. Phrasal verbs are multiword expressions used frequently in English, independent of the domain and degree of formality of language. They are challenging for natural language processing due to their idiosyncratic semantic and syntactic properties. The meaning of phrasal verbs is often not directly derivable from the semantics of their constituent tokens. In addition, they are hard to identify in text because of their flexible structure and due to ambiguous prepositional phrase attachments. The importance of the detection and special treatment of phrasal verbs is measured in the context of SMT, where the word-for-word translation of these units often produces incoherent results. I will present two ways of integrating phrasal verb information in a phrase-based SMT system. Automatic and manual evaluations of the results reveal improvements in the translation quality in both experiments.

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