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Register a new userSimultaneous Neural Machine Translation with Constituent Label Prediction
الترجمة الآلة العصبية في وقت واحد مع التنبؤ التسمية التأسيسي
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الترجمة المتزامنة هي مهمة تبدأ فيها الترجمة قبل انتهاء المتكلم من التحدث، لذلك من المهم أن تقرر متى تبدأ عملية الترجمة.ومع ذلك، فإن اتخاذ قرار بشأن قراءة المزيد من كلمات الإدخال أو بدء الترجمة من الصعب على أزواج اللغة مع أوامر كلمة مختلفة مثل اللغة الإنجليزية واليابانية.بدافع من مفهوم إعادة ترتيب المسبق، نقترح بضع قواعد قرارات بسيطة باستخدام تسمية التأسيس التالي المتوقع من خلال التنبؤ التسمي التأسيسي التدريجي.في تجارب على الترجمة الفورية الإنجليزية إلى اليابانية، الطريقة المقترحة تفوق خطوط الأساس في مفاضلة جودة الكمون.
Simultaneous translation is a task in which translation begins before the speaker has finished speaking, so it is important to decide when to start the translation process. However, deciding whether to read more input words or start to translate is difficult for language pairs with different word orders such as English and Japanese. Motivated by the concept of pre-reordering, we propose a couple of simple decision rules using the label of the next constituent predicted by incremental constituent label prediction. In experiments on English-to-Japanese simultaneous translation, the proposed method outperformed baselines in the quality-latency trade-off.
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In simultaneous machine translation, finding an agent with the optimal action sequence of reads and writes that maintain a high level of translation quality while minimizing the average lag in producing target tokens remains an extremely challenging
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