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Bangalore is often heralded as India’s future—a city where global technologies converge with multinational capital to produce a cosmopolitan workforce and vibrant economic growth. In this narrative the city’s main challenge revolves around its success: whether its physical infrastructure can support its burgeoning population. Most observers assume that Bangalore’s emergence as a “global city” represents its more complete integration into the world economy and, by extension, a more inclusive and cosmopolitan outlook among its growing middle class. Andrew C. Willford sheds light on a growing paradox: even as Bangalore has come to signify “progress” and economic possibility both...
This reader reveals how food habits and beliefs both present a microcosm of any culture and contribute to our understanding of human behaviour. Particular attention is given to how men and women define themselves differently through food choices.
Investigations into employing statistical approaches with linguistically motivated representations and its impact on Natural Language processing tasks. The last decade has seen computational implementations of large hand-crafted natural language grammars in formal frameworks such as Tree-Adjoining Grammar (TAG), Combinatory Categorical Grammar (CCG), Head-driven Phrase Structure Grammar (HPSG), and Lexical Functional Grammar (LFG). Grammars in these frameworks typically associate linguistically motivated rich descriptions (Supertags) with words. With the availability of parse-annotated corpora, grammars in the TAG and CCG frameworks have also been automatically extracted while maintaining th...
Extraordinary advances in machine translation over the last three quarters of a century have profoundly affected many aspects of the translation profession. The widespread integration of adaptive “artificially intelligent” technologies has radically changed the way many translators think and work. In turn, groundbreaking empirical research has yielded new perspectives on the cognitive basis of the human translation process. Translation is in the throes of radical transition on both professional and academic levels. The game-changing introduction of neural machine translation engines almost a decade ago accelerated these transitions. This volume takes stock of the depth and breadth of resulting developments, highlighting the emerging rivalry of human and machine intelligence. The gathering and analysis of big data is a common thread that has given access to new insights in widely divergent areas, from literary translation to movie subtitling to consecutive interpreting to development of flexible and powerful new cognitive models of translation.
Empirical research is carried out in a cyclic way: approaching a research area bottom-up, data lead to interpretations and ideally to the abstraction of laws, on the basis of which a theory can be derived. Deductive research is based on a theory, on the basis of which hypotheses can be formulated and tested against the background of empirical data. Looking at the state-of-the-art in translation studies, either theories as well as models are designed or empirical data are collected and interpreted. However, the final step is still lacking: so far, empirical data has not lead to the formulation of theories or models, whereas existing theories and models have not yet been comprehensively tested...
Drawing on the works of ten scholars and public intellectuals ranging over 200 years, this book foregrounds ways of knowing that include but go beyond the cognitive. The book explores the work of Harriet Martineau, Jane Addams, W. E. B. Du Bois, Zora Neale Hurston, Ella Deloria, M. N. Srinivas, Barbara Myerhoff, Orlando Fals Borda, Ronald Takaki and Nawal El Saadawi. The author discusses their multifaceted ethnographic practices and argues that such practices are still under-acknowledged in contemporary research in comparison to cognition and categorization. These scholars were outsiders to their societies in a variety of ways. They highlighted power imbalances in the perception and represen...
How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.
The revision comes 10 years after the first edition and completely overhauls the text not only in terms of look and feel but also content which is now contemporary while also being timeless. A large number of words are explained with the help of examples and their lineage which helps the reader understand their individual usage and the ways to use them on the correct occasion.
Experience in translation does not always correlate with the quality of the target text. Also, the evaluations of translation work vary considerably among evaluators. Why not shifting the focus of attention from the final translation to the underlying translation process when assessing translation competence? Iryna Kloster applies a multi-method approach to model the translation competence based on empirical parameters, such as gaze behavior, dictionary use, revisions as well as subjective evaluations of comprehension and translation difficulty. Eye tracking, keystroke logging, screen recording and retrospective interviews were applied to collect data in the experimental groups consisting of novice and semi-professional translators. As a consequence, the author suggests using language contrasts for researching translation competence. She draws conclusions based on hypotheses testing, provides justification by triangulating quantitative and qualitative data and discusses the results in the light of empirical translation studies as well.
Print edition of Lions District 317E Mini Directory for the year 2016-17, released by District Governor PMJF Lion Bharathi Nagesh. This Digital Edition is a replica of the book for reading in Mobile phones, Tablets and Lap Tops.