Buch, Englisch, 220 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 485 g
Buch, Englisch, 220 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 485 g
ISBN: 978-0-367-56199-4
Verlag: CRC Press
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.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie
- Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik Mathematik Algebra Zahlentheorie
Weitere Infos & Material
Preface. Introduction. Past Work on MT for Related Languages. I Machine Translation. Utilizing Lexical Similarity by using Subword Translation Units. Improving Subword-level. Translation Quality. Subword-level Pivot-based SMT. A Case Study on Indic Language Translation. II Machine Transliteration. Utilizing Orthographic Similarity for Unsupervised Transliteration. Multilingual Neural Transliteration. Conclusion and Future Directions. Appendices. A Extended ITRANS Romanization Scheme. B Software and Data Resources. C Conferences/Workshops for Translation between Related Languages. Bibliography.