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Register a new userOptimal Word Segmentation for Neural Machine Translation into Dravidian Languages
تجزئة الكلمات المثلى الترجمة الآلية العصبية إلى لغات Dravidian
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من الصعب للغاية ترجمة لغات Dravidian، مثل Kannada و Tamil، على ترجمة النماذج العصبية الحديثة.ينبع هذا من حقيقة أن هذه اللغات غنية بالمثل للغاية بالإضافة إلى توفير الموارد منخفضة الموارد.في هذه الورقة، نركز على تجزئة الكلمات الفرعية وتقييم الحد من المفردات الدوافع اللغوية (LMVR) مقابل الجملة الأكثر استخداما (SP) لمهمة الترجمة من اللغة الإنجليزية إلى أربعة لغات Dravidian مختلفة.بالإضافة إلى ذلك، نحقق في حجم المفردات الفرعية المثلى لكل لغة.نجد أن SP هو الخيار الأكثر شمولا للتجزئة، وأن أحجام القاموس الأكبر تؤدي إلى جودة الترجمة الأعلى.
Dravidian languages, such as Kannada and Tamil, are notoriously difficult to translate by state-of-the-art neural models. This stems from the fact that these languages are morphologically very rich as well as being low-resourced. In this paper, we focus on subword segmentation and evaluate Linguistically Motivated Vocabulary Reduction (LMVR) against the more commonly used SentencePiece (SP) for the task of translating from English into four different Dravidian languages. Additionally we investigate the optimal subword vocabulary size for each language. We find that SP is the overall best choice for segmentation, and that larger dictionary sizes lead to higher translation quality.
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