Over the past few years, neural networks have re-emerged as powerful machine-learning
models, yielding state-of-the-art results in fields such as image recognition and speech …

Deep learning is revolutionizing how machine translation systems are built today. This book
introduces the challenge of machine translation and evaluation-including historical …

This paper describes the development of a multilingual, manually annotated dataset for
three under-resourced Dravidian languages generated from social media comments. The …

The dream of automatic language translation is now closer thanks to recent advances in the
techniques that underpin statistical machine translation. This class-tested textbook from an …

A hybridised form of direct and rule-based language processing is used in this paper to
present a Machine translation system from Sanskrit to Hindi. The divergence between …

Languages help to unite the world socially, culturally and technologically. Different natives
communicate in different languages; there is a tremendous requirement for inter-language …

In this paper we explore the novel idea of building a single universal reordering model from
English to a large number of target languages. To build this model we exploit typological …

In machine translation (MT) that involves translating between two languages with significant
differences in word order, determining the correct word order of translated words is a major …

This chapter presents in detail the main translation process of PRESEMT, delving deeper in
the core of the system and its inner workings. All SMT systems (Koehn 2010), which …

Success of neural networks in natural language processing has paved the way for neural
machine translation (NMT), which rapidly became the mainstream approach in machine …