Traduction automatique neuronale multidomaine Aujourd'hui, les systèmes de traduction automatique neuronale (NMT) constituent des systèmes de pointe en traduction automatique (TA). Cependant, ces modèles de traduction nécessitent des données d'entraînement rel…
Optical Character Recognition (OCR) is one of the central problems in pattern recognition. Its applications have played a great role in the digitization of document images collected from het- erogeneous sources. Many of the well-known scripts have OCR systems…
Neural machine translation (NMT) has been shown to outperform statistical machine translation. However, NMT models typically require a large number of parameters and are expensive to train and deploy. Moreover, its large model size makes parallel training inef…
Neural machine translation (NMT) is a promising approach to the task of machine translation that has led to state-of-the-art results in many settings. However, NMT translations are still far from sufficient for many practical purposes. For this reason, there i…
This thesis aims for general robust Neural Machine Translation (NMT) that is agnostic to the test domain. NMT has achieved high quality on benchmarks with closed datasets such as WMT and NIST but can fail when the translation input contains noise due to, for e…
Effective fusion of data from multiple modalities, such as video, speech, and text, is a challenging task due to the heterogeneous nature of multimodal data. In this work, we propose fusion techniques that aim to model context from different modalities effecti…
ينبع هذا العمل من الرغبة في استكشاف مدى التقدم الذي حصل مؤخرا في مجال تقنيات التعلم الآلي في الترجمة الآلية. والغرض من هذه الدراسة هو اظهار التحسينات المستمرة في الذكاء الاصطناعي والذي اظهر نتائج مذهلة في مجال الترجمة
Title: Indonesian-English Neural Machine Translation Author: Meisyarah Dwiastuti Department: Institute of Formal and Applied Linguistics Supervisor: Mgr. Martin Popel, Ph.D., Institute of Formal and Applied Linguis- tics Abstract: In this thesis, we conduct a…
Typically it is seen that multimodal neural machine translation (MNMT) systems trained on a combination of visual and textual inputs produce better translations than systems trained using only textual inputs. The task of such systems can be decomposed into two…
Machine Translation, the subfield of Computer Science that focuses on translating between two human languages, has greatly benefited from neural networks. However, these neural machine translation systems have complicated architectures with many hyperparameters…
Machine translation (MT) is an important task in natural language processing as it automates the translation process and reduces the reliance on human translators. The goal of MT is to generate translations of a given text in a source language to that in the t…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
يجيب من قاعدة بيانات المستودع فقط، ولا يخترع سجلات أو أرقاماً. لا يُحفظ ما تكتبه على الخادم.
قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
