Buch, Englisch, Band 1922, 130 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 230 g
19th China Conference, CCMT 2023, Jinan, China, October 19-21, 2023, Proceedings
Buch, Englisch, Band 1922, 130 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 230 g
Reihe: Communications in Computer and Information Science
ISBN: 978-981-99-7893-9
Verlag: Springer Nature Singapore
This book constitutes the refereed proceedings of the 19th China Conference on Machine Translation, CCMT 2023, held in Jinan, China, during October 19–21, 2023.
The 8 full papers and 3 short papers included in this book were carefully reviewed and selected from 71 submissions. They focus on machine translation; improvement of translation models and systems; translation quality estimation; document-level machine translation; low-resource machine translation.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
- Mathematik | Informatik EDV | Informatik Angewandte Informatik
- Mathematik | Informatik EDV | Informatik Informatik Logik, formale Sprachen, Automaten
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Informationstheorie, Kodierungstheorie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
Weitere Infos & Material
Transn's submission for CCMT 2023 Quality Estimation Task.- HW-TSC's Neural Machine Translation System for CCMT 2023.- CCMT2023 Machine Translation Evaluation Technical Report.- Korean-Chinese Machine Translation Method Based on Independent Language Features.- NJUNLP's Submission for CCMT 2023 Quality Estimation Task.- HIT-MI&T Lab's Submission to CCMT 2023 Automatic Post-Editing Task.- A k-Nearest Neighbor Approach for Domain-Specific Translation Quality Estimation.- WSA: A Unified Framework for Word and Sentence Autocompletion in Interactive Machine Translation.- ISTIC's Neural Machine Translation Systems for CCMT'2023.- A Novel Dataset and Benchmark Analysis on Document Image Translation.- Joint Contrastive Learning for Factual Consistency Evaluation of Cross-Lingual Abstract Summarization.
