Machine Translation and Transliteration involving Related, Low-resource Languages
Machine Translation and Transliteration involving Related, Low-resource Languages

Author: Anoop Kunchukuttan

Publisher: CRC Press

Published: 2021-09-08

Total Pages: 215

ISBN-13: 1000422410

DOWNLOAD EBOOK

Machine Translation and Transliteration involving Related, Low-resource Languages discusses an important aspect of natural language processing that has received lesser attention: translation and transliteration involving related languages in a low-resource setting. This is a very relevant real-world scenario for people living in neighbouring states/provinces/countries who speak similar languages and need to communicate with each other, but training data to build supporting MT systems is limited. The book discusses different characteristics of related languages with rich examples and draws connections between two problems: translation for related languages and transliteration. It shows how linguistic similarities can be utilized to learn MT systems for related languages with limited data. It comprehensively discusses the use of subword-level models and multilinguality to utilize these linguistic similarities. The second part of the book explores methods for machine transliteration involving related languages based on multilingual and unsupervised approaches. Through extensive experiments over a wide variety of languages, the efficacy of these methods is established. Features Novel methods for machine translation and transliteration between related languages, supported with experiments on a wide variety of languages. An overview of past literature on machine translation for related languages. A case study about machine translation for related languages between 10 major languages from India, which is one of the most linguistically diverse country in the world. The book presents important concepts and methods for machine translation involving related languages. In general, it serves as a good reference to NLP for related languages. It is intended for students, researchers and professionals interested in Machine Translation, Translation Studies, Multilingual Computing Machine and Natural Language Processing. It can be used as reference reading for courses in NLP and machine translation. Anoop Kunchukuttan is a Senior Applied Researcher at Microsoft India. His research spans various areas on multilingual and low-resource NLP. Pushpak Bhattacharyya is a Professor at the Department of Computer Science, IIT Bombay. His research areas are Natural Language Processing, Machine Learning and AI (NLP-ML-AI). Prof. Bhattacharyya has published more than 350 research papers in various areas of NLP.

Machine Translation and Transliteration Involving Related and Low-resource Languages
Machine Translation and Transliteration Involving Related and Low-resource Languages

Author: Anoop Kunchukuttan

Publisher: Chapman & Hall/CRC

Published: 2021-08-12

Total Pages: 0

ISBN-13: 9781003096771

DOWNLOAD EBOOK

Machine Translation and Transliteration involving Related, Low-resource Languages discusses an important aspect of natural language processing that has received lesser attention: translation and transliteration involving related languages in a low-resource setting. This is a very relevant real-world scenario for people living in neighbouring states/provinces/countries who speak similar languages and need to communicate with each other, but training data to build supporting MT systems is limited. The book discusses different characteristics of related languages with rich examples and draws connections between two problems: translation for related languages and transliteration. It shows how linguistic similarities can be utilized to learn MT systems for related languages with limited data. It comprehensively discusses the use of subword-level models and multilinguality to utilize these linguistic similarities. The second part of the book explores methods for machine transliteration involving related languages based on multilingual and unsupervised approaches. Through extensive experiments over a wide variety of languages, the efficacy of these methods is established. Features Novel methods for machine translation and transliteration between related languages, supported with experiments on a wide variety of languages. An overview of past literature on machine translation for related languages. A case study about machine translation for related languages between 10 major languages from India, which is one of the most linguistically diverse country in the world. The book presents important concepts and methods for machine translation involving related languages. In general, it serves as a good reference to NLP for related languages. It is intended for students, researchers and professionals interested in Machine Translation, Translation Studies, Multilingual Computing Machine and Natural Language Processing. It can be used as reference reading for courses in NLP and machine translation. Anoop Kunchukuttan is a Senior Applied Researcher at Microsoft India. His research spans various areas on multilingual and low-resource NLP. Pushpak Bhattacharyya is a Professor at the Department of Computer Science, IIT Bombay. His research areas are Natural Language Processing, Machine Learning and AI (NLP-ML-AI). Prof. Bhattacharyya has published more than 350 research papers in various areas of NLP.

Machine Translation and Transliteration involving Related, Low-resource Languages
Machine Translation and Transliteration involving Related, Low-resource Languages

Author: Anoop Kunchukuttan

Publisher: CRC Press

Published: 2021-08-12

Total Pages: 220

ISBN-13: 100042166X

DOWNLOAD EBOOK

Machine Translation and Transliteration involving Related, Low-resource Languages discusses an important aspect of natural language processing that has received lesser attention: translation and transliteration involving related languages in a low-resource setting. This is a very relevant real-world scenario for people living in neighbouring states/provinces/countries who speak similar languages and need to communicate with each other, but training data to build supporting MT systems is limited. The book discusses different characteristics of related languages with rich examples and draws connections between two problems: translation for related languages and transliteration. It shows how linguistic similarities can be utilized to learn MT systems for related languages with limited data. It comprehensively discusses the use of subword-level models and multilinguality to utilize these linguistic similarities. The second part of the book explores methods for machine transliteration involving related languages based on multilingual and unsupervised approaches. Through extensive experiments over a wide variety of languages, the efficacy of these methods is established. Features Novel methods for machine translation and transliteration between related languages, supported with experiments on a wide variety of languages. An overview of past literature on machine translation for related languages. A case study about machine translation for related languages between 10 major languages from India, which is one of the most linguistically diverse country in the world. The book presents important concepts and methods for machine translation involving related languages. In general, it serves as a good reference to NLP for related languages. It is intended for students, researchers and professionals interested in Machine Translation, Translation Studies, Multilingual Computing Machine and Natural Language Processing. It can be used as reference reading for courses in NLP and machine translation. Anoop Kunchukuttan is a Senior Applied Researcher at Microsoft India. His research spans various areas on multilingual and low-resource NLP. Pushpak Bhattacharyya is a Professor at the Department of Computer Science, IIT Bombay. His research areas are Natural Language Processing, Machine Learning and AI (NLP-ML-AI). Prof. Bhattacharyya has published more than 350 research papers in various areas of NLP.

Addressing Issues of Learner Diversity in English Language Education
Addressing Issues of Learner Diversity in English Language Education

Author: Tran, Thao Quoc

Publisher: IGI Global

Published: 2024-04-22

Total Pages: 377

ISBN-13:

DOWNLOAD EBOOK

In the dynamic context of English language education, learners bring many differences in identity, motivation, engagement, ability, and more. Addressing Issues of Learner Diversity in English Language Education recognizes that traditional, one-size-fits-all approaches to language education are insufficient in meeting the needs of a varied and global learner population. It grapples with effectively teaching English to individuals with diverse linguistic backgrounds, learning styles, and cultural contexts. The challenges range from learner autonomy and motivation issues to navigating mixed-level classes and integrating technology into language teaching. Drawing on current research trends and cutting-edge methodologies, this book captures the diverse voices of contributors from various ESL/EFL settings, offering context-specific solutions to the myriad challenges faced in language education. The book illuminates the nuanced phenomena within English language education; it showcases innovative theoretical frameworks and up-to-date research findings. By addressing learners as singular individuals and collectives, the publication guides educators in enhancing individual competencies and maximizing the potential of each learner.

Empowering Low-Resource Languages With NLP Solutions
Empowering Low-Resource Languages With NLP Solutions

Author: Pakray, Partha

Publisher: IGI Global

Published: 2024-02-27

Total Pages: 328

ISBN-13:

DOWNLOAD EBOOK

In our increasingly interconnected world, low-resource languages face the threat of oblivion. These linguistic gems, often spoken by marginalized communities, are at risk of fading away due to limited data and resources. The neglect of these languages not only erodes cultural diversity but also hinders effective communication, education, and social inclusion. Academics, practitioners, and policymakers grapple with the urgent need for a comprehensive solution to preserve and empower these vulnerable languages. Empowering Low-Resource Languages With NLP Solutions is a pioneering book that stands as the definitive answer to the pressing problem at hand. It tackles head-on the challenges that low-resource languages face in the realm of Natural Language Processing (NLP). Through real-world case studies, expert insights, and a comprehensive array of topics, this book equips its readers—academics, researchers, practitioners, and policymakers—with the tools, strategies, and ethical considerations needed to address the crisis facing low-resource languages.

Computational Intelligence in Communications and Business Analytics
Computational Intelligence in Communications and Business Analytics

Author: Somnath Mukhopadhyay

Publisher: Springer Nature

Published: 2022-07-21

Total Pages: 460

ISBN-13: 3031107667

DOWNLOAD EBOOK

This book constitutes the refereed proceedings of the 4th International Conference on Computational Intelligence, Communications, and Business Analytics, CICBA 2022, held in Silchar, India, in January 2022. The 21 full papers and 13 short papers presented in this volume were carefully reviewed and selected from 107 submissions. The papers are organized in topical sections on computational intelligence; computational intelligence in communication; and computational intelligence in analytics.

Neural Machine Translation
Neural Machine Translation

Author: Philipp Koehn

Publisher: Cambridge University Press

Published: 2020-06-18

Total Pages: 409

ISBN-13: 1108497322

DOWNLOAD EBOOK

Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.

Computational Linguistics and Intelligent Text Processing
Computational Linguistics and Intelligent Text Processing

Author: Alexander Gelbukh

Publisher: Springer

Published: 2018-03-20

Total Pages: 652

ISBN-13: 3319754874

DOWNLOAD EBOOK

The two-volume set LNCS 9623 + 9624 constitutes revised selected papers from the CICLing 2016 conference which took place in Konya, Turkey, in April 2016. The total of 89 papers presented in the two volumes was carefully reviewed and selected from 298 submissions. The book also contains 4 invited papers and a memorial paper on Adam Kilgarriff’s Legacy to Computational Linguistics. The papers are organized in the following topical sections: Part I: In memoriam of Adam Kilgarriff; general formalisms; embeddings, language modeling, and sequence labeling; lexical resources and terminology extraction; morphology and part-of-speech tagging; syntax and chunking; named entity recognition; word sense disambiguation and anaphora resolution; semantics, discourse, and dialog. Part II: machine translation and multilingualism; sentiment analysis, opinion mining, subjectivity, and social media; text classification and categorization; information extraction; and applications.

Iaeng Transactions On Engineering Sciences: Special Issue For The International Association Of Engineers Conferences 2015
Iaeng Transactions On Engineering Sciences: Special Issue For The International Association Of Engineers Conferences 2015

Author: Sio-iong Ao

Publisher: World Scientific

Published: 2016-08-10

Total Pages: 469

ISBN-13: 9813142731

DOWNLOAD EBOOK

Two large international conferences on Advances in Engineering Sciences were held in Hong Kong, March 18-20, 2015, under the International MultiConference of Engineers and Computer Scientists (IMECS 2015), and in London, UK, 1-3 July, 2015, under the World Congress on Engineering (WCE 2015) respectively. This volume contains 35 revised and extended research articles written by prominent researchers participating in the conferences. Topics covered include engineering mathematics, computer science, electrical engineering, manufacturing engineering, industrial engineering, and industrial applications. The book offers state-of-the-art advances in engineering sciences and also serves as an excellent reference work for researchers and graduate students working with/on engineering sciences.

Machine Translation
Machine Translation

Author: Pushpak Bhattacharyya

Publisher: CRC Press

Published: 2015-02-04

Total Pages: 261

ISBN-13: 1439897190

DOWNLOAD EBOOK

This book compares and contrasts the principles and practices of rule-based machine translation (RBMT), statistical machine translation (SMT), and example-based machine translation (EBMT). Presenting numerous examples, the text introduces language divergence as the fundamental challenge to machine translation, emphasizes and works out word alignment, explores IBM models of machine translation, covers the mathematics of phrase-based SMT, provides complete walk-throughs of the working of interlingua-based and transfer-based RBMT, and analyzes EBMT, showing how translation parts can be extracted and recombined to automatically translate a new input.