The Bottom Translation represents the first critical attempt at applying the ideas and methods of the great Russian critic, Mikhail Bakhtin, to the works of Shakespeare and other Elizabethans. Professor Kott uncovers the cultural and mythopoetic traditions underlying A Midsummer Night's Dream, The Tempest, Dr. Faustus, and other plays. His method draws him to interpret these works in the light of the carnival and popular tradition as it was set forth by Bakhtin. The Bottom Translation breaks new ground in critical thinking and theatrical vision and is an invaluable source of new ideas and perspectives. Included in this volume is also an extraordinary essay on Kurosawa's "Ran" in which the Japanese filmmaker recreates King Lear.

How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.

Focusing on multimodality in translation studies, this edited volume provides insights into the trends and practices of multimodal translation in a variety of media. Divided into four main themes, the book explores audiovisual translation in digital media, multimodal translation of Chinese classics, multimodal design in website translation, and the use of paratexts in conference interpreting. Contributors draw on a diverse range of methods and theoretical models, including systemic functional multimodal discourse analysis, narrative theory, Skopos-functional theory, multimodal analysis of digital discourse, and corpus-based multimodal analysis. It covers important topics in media translation, ranging from emerging multimodal translation models to multimodal creativity in interlingual subtitling for social media and identity construction in the multimodal translation of food advertising. Through robust empirical studies, the book aims to shed light on the methodological development of multimodal translation in different media forms, including social media, websites, on-site interactions and books. The title will be of great value to scholars and students of linguistics, translation studies, multimodal discourse analysis and digital media.

This book is the first volume that focuses on the specific challenges of machine translation with Arabic either as source or target language. It nicely fills a gap in the literature by covering approaches that belong to the three major paradigms of machine translation: Example-based, statistical and knowledge-based. It provides broad but rigorous coverage of the methods for incorporating linguistic knowledge into empirical MT. The book brings together original and extended contributions from a group of distinguished researchers from both academia and industry. It is a welcome and much-needed repository of important aspects in Arabic Machine Translation such as morphological analysis and syntactic reordering, both central to reducing the distance between Arabic and other languages. Most of the proposed techniques are also applicable to machine translation of Semitic languages other than Arabic, as well as translation of other languages with a complex morphology.