Natural Language Processing (NLP) is a subfield of artificial intelligence focused on processing and interpreting human language. With the recent success of NLP approaches across a diverse range of application areas, such as machine translation and sentiment a…
This study aims to highlight the role of machine translation and film dubbing using artificial intelligence technologies. It does so by analyzing machine translation as a tool to enhance the understanding of texts and translate them accurately and quickly, and…
The recent success of large neural network models trained on massive amounts of unlabeled data has, yet again, highlighted the power of scaling, in terms of both model capacity and data quantity. However, despite its successes, scaling up also adds new additio…
These days it is becoming common to communicate with international people as globalization expands.Although many international conferences are held, not all the speakers and listeners are good at English.Therefore, interpreters sometimes attend such conference…
[ES] En la última década, el reconocimiento automático del habla (RAH) y la traducción automática (TA) han mejorado enormemente mediante el uso de modelos de redes neuronales profundas (RNP) en constante evolución. Si a principios de los 2010 los sistemas de R…
Artificial intelligence (AI) impresses us daily, outperforming humans in complex games and tasks. Yet, AI and Large Language Models (LLMs) stumble to grasp a language that is thousands of years old. It's Arabic, where subtle diacritical marks can completely al…
Language is the pathway to democratize the boundary of land and culture. Bridging the gap between languages is one of the biggest challenges of Artificial Intelligent (AI) systems. The current success of AI systems is dominated by the supervised learning parad…
The advances in deep learning have led to great achievements in many Natural Language Processing (NLP) tasks. With the nature of language, i.e., sequential data, most NLP tasks can be framed into the sequence learning framework, such as text generation. As one…
Transformers are machine learning models designed to learn and predict sequential and structured data, which are crucial to tasks such as neural machine translation and semantic parsing.They have become state-of-the-art engines for both of these tasks and much…
In recent years, a number of mehtods for improving the decoding speed of neural machine translation systems have emerged. One of the approaches that pro- poses fundamental changes to the model architecture are non-autoregressive models. In standard autoregress…
With the advent of deep neural networks in recent years, Neural Machine Translation (NMT) systems have achieved state-of-the-art performance on standard translation benchmarks. NMT is a way to translate from one language to another with a single neural network…
(English) Gender bias is a dangerous form of social bias impacting an essential group of people. The effect of gender bias is propagated to our data, causing the accuracy of the predictions in models to be different depending on gender. In the deep learning er…
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.
