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Bottom-up approach to translate Tunisian dialect texts in Social Networks | IEEE Conference Publication | IEEE Xplore

Bottom-up approach to translate Tunisian dialect texts in Social Networks


Abstract:

Dialect translation is a motivating task for both industrial and academic fields. Indeed, migrating to a standard language facilitates communication between people throug...Show More

Abstract:

Dialect translation is a motivating task for both industrial and academic fields. Indeed, migrating to a standard language facilitates communication between people throughout the world, and facilitates application of Natural Language Processing tasks such as automatic opinion analysis, semantic analysis, etc. We describe, in this work, an effort to build a Neural Machine Translation (NMT) model in order to translate the comments posted on social media intended for the Tunisian community. It is a question of dealing with the Tunisian dialect (TD) in Social Networks (SN). Due to the orthographic ambiguity presented by the TD, we experiment different configurations corpora and NMT models following a bottom-up approach. The best configuration resulted in building a translation model which achieved a BLEU score of 69.22% on a test corpus.
Date of Conference: 05-08 December 2022
Date Added to IEEE Xplore: 20 January 2023
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Conference Location: Abu Dhabi, United Arab Emirates

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