Work

The Helsinki-NLP Submissions at NADI 2023 Shared Task: Walking the Baseline

Year: 2023

Type: conference-paper

Abstract: The Helsinki-NLP team participated in the NADI 2023 shared tasks on Arabic dialect translation with seven submissions.We used statistical (SMT) and neural machine translation (NMT) methods and explored characterand subword-based data preprocessing.Our submissions placed second in both tracks.In the open track, our winning submission is a character-level SMT system with additional Modern Standard Arabic language models.In the closed track, our best BLEU scores were obtained with the leave-as-is baseline, a simple copy of the input, and narrowly followed by SMT systems.In both tracks, fine-tuning existing multilingual models such as AraT5 or ByT5 did not yield superior performance compared to SMT.

Source: Arabic Natural Language Processing Conference (ArabicNLP)

DOI: 10.18653/v1/2023.arabicnlp-1.73

Authors: Yves Scherrer, Aleksandra Miletić, Olli Kuparinen

Institutions: University of Helsinki, University of Oslo, Tampere University, University of Tampere

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: China Scholarship Council

OpenAlex ID: W4389518338