Titlebook: Machine Translation; 16th China Conferenc Junhui Li,Andy Way Conference proceedings 2020 Springer Nature Singapore Pte Ltd. 2020 artificial

駁船

YuQ: A Chinese-Uyghur Medical-Domain Neural Machine Translation Dataset Towards Knowledge-Driven,ing model, we can win the challenge of low translation accuracy in Chinese-Uyghur machine translation professional terms. We provide several benchmark models. Ablation study results show that the models can be enhanced by introducing domain knowledge.

古文字學(xué)

灌輸

Minatory

MTNER: A Corpus for Mongolian Tourism Named Entity Recognition,ain BERT representations with the 10?GB of unannotated Mongolian corpus, and trained a NER model based on the BERT tagging model with the newly corpus. Which achieves an overall 82.09 F1 score on Mongolian Tourism Named Entity Recognition and lead to an absolute increase of +3.54 F1 score over the traditional CRF Named Entity Recognition method.

心胸狹窄

Tencent Submissions for the CCMT 2020 Quality Estimation Task,and Transformer-estimator are conducted and two novel strategies, i.e. top-K strategy and multi-head attention strategy, are proposed to enhance the sentence feature representation. We also propose new effective ensemble technique for sentence-level predictions.

Inclement

Neural Machine Translation Based on Back-Translation for Multilingual Translation Evaluation Task, We also implemented multi-model ensemble technique to further boost the final result. Experiments show that our machine translation system achieved high accuracy without relying on any bilingual training data.

TIGER

Institution

congenial

Hui Huang,Hui Di,Jin’an Xu,Kazushige Ouchi,Yufeng Chenlassical test theory (CTT) and related practices. Beginning slowly in the 1940s and 1950s with the pioneering work of Frederic Lord, Allan Birnbaum, and GeorgRasch,bythe1970sthemeasurementjournalswerefullofimpo978-1-4419-1903-8978-0-387-29054-6Series ISSN 2199-7357 Series E-ISSN 2199-7365

欲望