Abstract:
Machine Translation (MT) refers to the use of computers for the task of translating automat
ically from one language to another. The differences between languages and especially the
inherent ambiguity of language make MT a very difficult problem. Traditional approaches to
MT have relied on humans supplying linguistic knowledge in the form of rules to transform
text in one language to another. Given the vastness of language, this is a highly knowledge
intensive task. Statistical MT is a radically different approach that automatically acquires
knowledge from large amounts of training data. This knowledge, which is typically in the
form of probabilities of various language features, is used to guide the translation process.
This report provides an overview of MT techniques, and looks in detail at the basic statisti
cal model.
Description:
We are thankful to Almighty Allah for his blessings for the successful completion of our
thesis. Our heartiest gratitude, profound indebtedness and deep respect go to our supervi
sor Dr. Mohammad Nurul Huda, Associate Professor and MSCSE Coordinator, Dept. of
CSE, (United International University), UIU Bhaban, House-80, Road-8/A, Satmasjid Road,
Dhanmondi, Dhaka-1209, Bangladesh, for his constant supervision, affectionate guidance
and great encouragement and motivation. His keen interest on the topic and valuable advices
throughout the study was of great help in completing thesis.
We are especially grateful to the Department of Computer Science and Engineering (CSE)
of Military Institute of Science and Technology (MIST) for providing their all out support
during the thesis work.
Finally, we would like to thank our families and our course mates for their appreciable
assistance, patience and suggestions during the course of our thesis.
