This book constitutes the refereed proceedings of the 13th China Workshop on Machine Translation, CWMT 2017, held in Dalian, China, in September 2017. The 10 papers presented in this volume were carefully reviewed and selected from 26 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
This book constitutes the refereed proceedings of the 13th China Workshop on Machine Translation, CWMT 2017, held in Dalian, China, in September 2017. The 10 papers presented in this volume were carefully reviewed and selected from 26 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
Produktdetails
Produktdetails
Communications in Computer and Information Science 787
Neural Machine Translation with Phrasal Attention.- Singleton Detection for Coreference Resolution via Multi-window and Multi-Filter CNN.- A Method of Unknown Words Processing for Neural Machine Translation Using HowNet.- Word, Subword or Character? An Empirical Study of Granularity in Chinese-English NMT.- An Unknown Word Processing Method in NMT by Integrating Syntactic Structure and Semantic Concept.- RGraph: Generating Reference Graphs for Better Machine Translation Evaluation.- ENTF: An Entropy-based MT Evaluation Metric.- Translation Oriented Sentence Level Collocation Identification and Extraction.- Combining Domain Knowledge and Deep Learning Makes NMT More Adaptive.- Handling Many-To-One UNK Translation for Neural Machine Translation.- A Content-based Neural Reordering Model for Statistical Machine Translation.
Neural Machine Translation with Phrasal Attention.- Singleton Detection for Coreference Resolution via Multi-window and Multi-Filter CNN.- A Method of Unknown Words Processing for Neural Machine Translation Using HowNet.- Word, Subword or Character? An Empirical Study of Granularity in Chinese-English NMT.- An Unknown Word Processing Method in NMT by Integrating Syntactic Structure and Semantic Concept.- RGraph: Generating Reference Graphs for Better Machine Translation Evaluation.- ENTF: An Entropy-based MT Evaluation Metric.- Translation Oriented Sentence Level Collocation Identification and Extraction.- Combining Domain Knowledge and Deep Learning Makes NMT More Adaptive.- Handling Many-To-One UNK Translation for Neural Machine Translation.- A Content-based Neural Reordering Model for Statistical Machine Translation.
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