Enlarging Monolingual Dictionaries for Machine Translation with Active Learning and Non-Expert Users

This paper explores a new approach to help non-expert users with no background in linguistics to add new words to a monolingual dictionary in a rule-based machine translation system. Our method aims at choosing the correct paradigm which explains not only the particular surface form introduced by the user, but also the rest of inflected forms of the word. A large monolingual corpus is used to extract an initial set of potential paradigms, which are then interactively refined by the user through active machine learning. We show the results of experiments performed on a Spanish monolingual dictionary.

Enlarging monolingual dictionaries for machine translation with active learning and non-expert users

This paper explores a new approach to help non-expert users with no background in linguistics to add new words to a monolingual dictionary in a rule-based machine translation system. Our method aims at choosing the correct paradigm which explains not only the particular surface form introduced by the user, but also the rest of inflected forms of the word. A large monolingual corpus is used to extract an initial set of potential paradigms, which are then interactively refined by the user through active machine learning. We show the results of experiments performed on a Spanish monolingual dictionary.