Hybrid Machine Translation For Low Resource Languages PDF Download
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Author | : George Joe |
Publisher | : |
Total Pages | : 0 |
Release | : 2023-11-02 |
Genre | : Art |
ISBN | : |
Download Hybrid Machine Translation for Low-Resource Languages Book in PDF, ePub and Kindle
The book "Hybrid Machine Translation for Low-Resource Languages" authored by George Joe provides a comprehensive overview of the development and evaluation of hybrid machine translation systems for English to Indian languages under low-resource conditions. The book discusses the challenges faced in developing machine translation systems for low-resource languages and how hybrid approaches can be used to overcome these challenges. The author presents a detailed analysis of various hybrid machine translation techniques such as rule-based, statistical, and neural machine translation, and how these techniques can be integrated to improve translation quality and efficiency. The book also covers the use of machine learning techniques such as transfer learning and active learning to improve the performance of machine translation systems. The book provides numerous case studies and practical examples of the development and evaluation of hybrid machine translation systems for low-resource languages. The author also discusses the importance of creating parallel corpora for low-resource languages and the challenges involved in creating such corpora. This book is a valuable resource for researchers and practitioners working in the field of natural language processing, machine learning, and machine translation. It provides a comprehensive understanding of the challenges involved in developing machine translation systems for low-resource languages and the ways in which hybrid approaches can be used to overcome these challenges. It also highlights the importance of creating parallel corpora for low-resource languages to improve the performance of machine translation systems.
Author | : Petra Perner |
Publisher | : Springer |
Total Pages | : 0 |
Release | : 2018-07-08 |
Genre | : Computers |
ISBN | : 9783319961323 |
Download Machine Learning and Data Mining in Pattern Recognition Book in PDF, ePub and Kindle
This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.
Author | : Marta R. Costa-jussà |
Publisher | : Springer |
Total Pages | : 205 |
Release | : 2016-07-12 |
Genre | : Computers |
ISBN | : 3319213113 |
Download Hybrid Approaches to Machine Translation Book in PDF, ePub and Kindle
This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are achieved by combining data-driven and rule-based techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical approaches to MT, the incorporation of data-driven components into rule-based approaches, or statistical and rule-based pre- and post-processing for both types of MT architectures. The book is of interest primarily to MT specialists, but also – in the wider fields of Computational Linguistics, Machine Learning and Data Mining – to translators and managers of translation companies and departments who are interested in recent developments concerning automated translation tools.
Author | : Anoop Kunchukuttan |
Publisher | : CRC Press |
Total Pages | : 215 |
Release | : 2021-09-08 |
Genre | : Computers |
ISBN | : 1000422410 |
Download Machine Translation and Transliteration involving Related, Low-resource Languages Book in PDF, ePub and Kindle
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.
Author | : L. Ashok Kumar |
Publisher | : John Wiley & Sons |
Total Pages | : 500 |
Release | : 2024-05-07 |
Genre | : Computers |
ISBN | : 1394213581 |
Download Automatic Speech Recognition and Translation for Low Resource Languages Book in PDF, ePub and Kindle
AUTOMATIC SPEECH RECOGNITION and TRANSLATION for LOW-RESOURCE LANGUAGES This book is a comprehensive exploration into the cutting-edge research, methodologies, and advancements in addressing the unique challenges associated with ASR and translation for low-resource languages. Automatic Speech Recognition and Translation for Low Resource Languages contains groundbreaking research from experts and researchers sharing innovative solutions that address language challenges in low-resource environments. The book begins by delving into the fundamental concepts of ASR and translation, providing readers with a solid foundation for understanding the subsequent chapters. It then explores the intricacies of low-resource languages, analyzing the factors that contribute to their challenges and the significance of developing tailored solutions to overcome them. The chapters encompass a wide range of topics, ranging from both the theoretical and practical aspects of ASR and translation for low-resource languages. The book discusses data augmentation techniques, transfer learning, and multilingual training approaches that leverage the power of existing linguistic resources to improve accuracy and performance. Additionally, it investigates the possibilities offered by unsupervised and semi-supervised learning, as well as the benefits of active learning and crowdsourcing in enriching the training data. Throughout the book, emphasis is placed on the importance of considering the cultural and linguistic context of low-resource languages, recognizing the unique nuances and intricacies that influence accurate ASR and translation. Furthermore, the book explores the potential impact of these technologies in various domains, such as healthcare, education, and commerce, empowering individuals and communities by breaking down language barriers. Audience The book targets researchers and professionals in the fields of natural language processing, computational linguistics, and speech technology. It will also be of interest to engineers, linguists, and individuals in industries and organizations working on cross-lingual communication, accessibility, and global connectivity.
Author | : L. Ashok Kumar |
Publisher | : John Wiley & Sons |
Total Pages | : 428 |
Release | : 2024-03-28 |
Genre | : Computers |
ISBN | : 1394214170 |
Download Automatic Speech Recognition and Translation for Low Resource Languages Book in PDF, ePub and Kindle
AUTOMATIC SPEECH RECOGNITION and TRANSLATION for LOW-RESOURCE LANGUAGES This book is a comprehensive exploration into the cutting-edge research, methodologies, and advancements in addressing the unique challenges associated with ASR and translation for low-resource languages. Automatic Speech Recognition and Translation for Low Resource Languages contains groundbreaking research from experts and researchers sharing innovative solutions that address language challenges in low-resource environments. The book begins by delving into the fundamental concepts of ASR and translation, providing readers with a solid foundation for understanding the subsequent chapters. It then explores the intricacies of low-resource languages, analyzing the factors that contribute to their challenges and the significance of developing tailored solutions to overcome them. The chapters encompass a wide range of topics, ranging from both the theoretical and practical aspects of ASR and translation for low-resource languages. The book discusses data augmentation techniques, transfer learning, and multilingual training approaches that leverage the power of existing linguistic resources to improve accuracy and performance. Additionally, it investigates the possibilities offered by unsupervised and semi-supervised learning, as well as the benefits of active learning and crowdsourcing in enriching the training data. Throughout the book, emphasis is placed on the importance of considering the cultural and linguistic context of low-resource languages, recognizing the unique nuances and intricacies that influence accurate ASR and translation. Furthermore, the book explores the potential impact of these technologies in various domains, such as healthcare, education, and commerce, empowering individuals and communities by breaking down language barriers. Audience The book targets researchers and professionals in the fields of natural language processing, computational linguistics, and speech technology. It will also be of interest to engineers, linguists, and individuals in industries and organizations working on cross-lingual communication, accessibility, and global connectivity.
Author | : Anoop Kunchukuttan |
Publisher | : |
Total Pages | : 199 |
Release | : 2022 |
Genre | : Machine translating |
ISBN | : 9780367562007 |
Download Machine Translation and Transliteration Involving Related and Low-resource Languages Book in PDF, ePub and Kindle
"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."--Publisher
Author | : Petra Perner |
Publisher | : Springer |
Total Pages | : 499 |
Release | : 2018-07-09 |
Genre | : Computers |
ISBN | : 3319961330 |
Download Machine Learning and Data Mining in Pattern Recognition Book in PDF, ePub and Kindle
This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.
Author | : Alexander Gelbukh |
Publisher | : Springer Science & Business Media |
Total Pages | : 662 |
Release | : 2007-02-07 |
Genre | : Computers |
ISBN | : 354070938X |
Download Computational Linguistics and Intelligent Text Processing Book in PDF, ePub and Kindle
This book constitutes the refereed proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2007, held in Mexico City, Mexico in February 2007. The 53 revised full papers presented together with 3 invited papers cover all current issues in computational linguistics research and present intelligent text processing applications.
Author | : Philipp Koehn |
Publisher | : Cambridge University Press |
Total Pages | : 409 |
Release | : 2020-06-18 |
Genre | : Computers |
ISBN | : 1108497322 |
Download Neural Machine Translation Book in PDF, ePub and Kindle
Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.