Machine translation (MT) models usually translate a text by considering isolated sentences based on a strict assumption that the sentences in a text are independent of one another. However, it is a truism that texts have properties of connectedness that go bey…
Being able to generate summaries automatically could speed up the spread and retention of information and potentially increase productivity in several fields. Using RNN-based encoder-decoder models with attention have been successful on a variety of language-r…
Machine translation (MT) investigates the use of software to translate a source sentence into the corresponding target sentence.The state-of-the-art MT approach is statistical MT, which learns statistical models from a parallel bilingual corpus to model the tr…
Machine Translation (MT) for language pairs with long distance dependencies and word reordering, such as German–English, is prone to producing output that is lexically or syntactically incoherent. Statistical MT (SMT) models used explicit or latent syntax to i…
Traduction automatique neuronale factorisée La diversité des langues complexifie la tâche de communication entre les humains à travers les différentes cultures. La traduction automatique est un moyen rapide et peu coûteux pour simplifier la communication inter…
[EN] High quality translations are in high demand these days. Although machine translation offers acceptable performance, it is not sufficient in some cases and human supervision is required. In order to ease the translation task of the human, machine translat…
Both Statistical Machine Translation and Neural Machine Translation (NMT) are data-dependent learning approaches to Machine Translation (MT). The prerequisite is a large volume of training data in order to generate good statistical models. However, even if lar…
Language models play an important role in many natural language processing tasks. In this thesis, we focus on language models built on artificial neural net- works. We examine the possibilities of using morphological annotations in these models. We propose a n…
This thesis addresses some of the challenges of translating morphologically rich languages (MRLs). Words in MRLs have more complex structures than those in other languages, so that a word can be viewed as a hierarchical structure with several internal subunits…
Neural machine translation is a resent approach to machine translation. Neural machine translation uses an artificial neural network to learn and perform translations. Usually an encoder-decoder architecture is used for the neural network. The encoder encodes…
Neural Machine Translation is a newly emerging approach to machine translation which attempts to build and train a large neural network that reads a sentence and outputs a notable translation. Nowadays the performance of such machines is in- creasingly in dema…
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.
