Search Results for author: Byeongil Ko

Found 3 papers, 0 papers with code

Auxiliary Sequence Labeling Tasks for Disfluency Detection

no code implementations24 Oct 2020 Dongyub Lee, Byeongil Ko, Myeong Cheol Shin, Taesun Whang, Daniel Lee, Eun Hwa Kim, EungGyun Kim, Jaechoon Jo

Existing works for disfluency detection have focused on designing a single objective only for disfluency detection, while auxiliary objectives utilizing linguistic information of a word such as named entity or part-of-speech information can be effective.

named-entity-recognition Named Entity Recognition +4

Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization

no code implementations COLING 2020 Dongyub Lee, Myeongcheol Shin, Taesun Whang, Seungwoo Cho, Byeongil Ko, Daniel Lee, EungGyun Kim, Jaechoon Jo

In this paper, we propose evaluation metrics that reflect semantic meanings of a reference summary and the original document, Reference and Document Aware Semantic Score (RDASS).

Text Summarization

SYSTRAN's Pure Neural Machine Translation Systems

no code implementations18 Oct 2016 Josep Crego, Jungi Kim, Guillaume Klein, Anabel Rebollo, Kathy Yang, Jean Senellart, Egor Akhanov, Patrice Brunelle, Aurelien Coquard, Yongchao Deng, Satoshi Enoue, Chiyo Geiss, Joshua Johanson, Ardas Khalsa, Raoum Khiari, Byeongil Ko, Catherine Kobus, Jean Lorieux, Leidiana Martins, Dang-Chuan Nguyen, Alexandra Priori, Thomas Riccardi, Natalia Segal, Christophe Servan, Cyril Tiquet, Bo wang, Jin Yang, Dakun Zhang, Jing Zhou, Peter Zoldan

Since the first online demonstration of Neural Machine Translation (NMT) by LISA, NMT development has recently moved from laboratory to production systems as demonstrated by several entities announcing roll-out of NMT engines to replace their existing technologies.

Machine Translation NMT +1

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