‫ بهبود ترجمه ماشینی مبتنی بر قاعده با استفاده از قواعد نحوی آماری

بهبود ترجمه ماشینی مبتنی بر قاعده با استفاده از قواعد نحوی آماری

حکیمه فدائی, هشام فیلی, فرناز قاسمی تودشکی

چکیده

ترجمه ماشینی مبتنی بر قاعده از مجموعه‌ای از قواعد که دربردارنده اطلاعات زبانی هستند در فرایند ترجمه استفاده می‌کند. نتایج تولید شده توسط این مترجم‌ها معمولاً از نظر دستور زبان و ترتیب کلمات بهتر از نتایج مترجم‌های آماری هستند. ولی تحقیقات نشان داده است که این ترجمه‌ها از نظر روانی و انتخاب کلمات مناسب، ضعیف‌تر از مترجم‌های آماری هستند. در این مقاله هدف، بهبود انتخاب لغات در مترجم مبتنی بر قاعده است. این کار با استفاده از مجموعه‌ای از قواعد نحوی- لغوی مبتنی بر گرامر درخت- پیوندی (TAG) انجام می‌شود. این قواعد احتمالاتی به‌صورت آماری از یک پیکره موازی با اندازه بزرگ استخراج شده‌اند. در سیستم ارائه شده، کلمات با ترتیب پیشنهادی مترجم مبتنی بر قاعده در زبان مقصد قرار می‌گیرند و به همین دلیل در ترجمه جملات از یک رمزگشای یکنواخت مبتنی بر برنامه‌ریزی پویا استفاده شده است. در این سیستم بهترین ترجمه با استناد به احتمال قواعد استفاده شده و امتیاز مدل زبانی انتخاب می‌شود. آزمایش‌ها روی ترجمه انگلیسی به فارسی نشان داد که کیفیت نتایج به‌دست ‌آمده از روش پیشنهادی حدود 3/1+ واحد بلو از کیفیت ترجمه به‌دست ‌آمده توسط مبتنی بر قاعده پایه بالاتر است.

کلمات کلیدی

ترجمه ماشینی ترکیبی, ترجمه ماشینی مبتنی بر قاعده, قواعد آماری, قواعد نحوی-لغوی, گرامر درخت-پیوندی

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