The 15th China Conference on Machine Translation (CCMT 2019), organized by the Chinese Information Processing Society of China, will be held at Jiangxi Normal University, China, on September 27-29, 2019. CCMT aims at providing a forum to facilitate communication and academic exchanges among domestic and foreign scholars on the latest developments in the field of MT. The previous fourteen events were successfully held by various institutes and universities (previously known as CWMT). Among these, several activities and shared tasks were successfully organized, including eight machine translation evaluations, an open-source software development (2006), and two strategic planning meetings (2010, 2012) as well. CCMT plays an important role in strengthening and promoting the research and development of Machine Translation (MT) in China, and it has become a leading academic activity in the field of Natural Language Processing (NLP).
CCMT 2019 features keynote speeches delivered by renowned experts in the field of MT, tutorials for students and young scholars, and panel sessions with academic and industry experts. System exhibition will be held during the conference to bring together the end-users, system developers and researchers of MT. This conference will provide a great opportunity to share and exchange valuable experiences on MT, and thus advance MT research and development in the region. CCMT 2019 will also continue the MT evaluations including bilingual translation tasks (Chinese-to-English, English-to-Chinese, Uyghur-to-Chinese, Tibetan-to-Chinese and Mongolian-to-Chinese), multilingual translation tasks (English, Chinese and Japanese), a speech translation task (Chinese-to-English) and quality estimation tasks (Chinese-to-English and English-to-Chinese).
The CCMT 2019 conference invites the submission of papers on substantial, original and unpublished research. A best paper award will be granted during the conference.
Papers are invited on all aspects of MT and NLP, including, but not limited to:
◆Dictionary, corpus processing and tool development for machine translation
◆Machine translation models and methods, including rule-based, example-based, statistical and neural machine translation
◆Pre-processing and post-processing for machine translation
◆Multi-engine translation system
◆Machine translation evaluation methodologies
◆Fundamental technologies for machine translation, such as word alignment, phrase extraction, name entity recognition and translation, lexical analysis, parsing, semantic analysis and document analysis for machine translation
◆Machine translation applications, including cross-language information retrieval, computer-assisted translation, embedded translation, multilingual dialogue and speech translation
◆Machine translation of low-resourced languages
◆Challenges and opportunities for machine translation in Internet era
CCMT 2019 allows authors submit manuscripts to leading international conferences in NLP (e.g., EMNLP) at same time. CCMT welcome submissions as either long or short papers. The number of pages should be 10-12 pages for long paper and 6 pages for short paper.
CCMT invites submissions in either Chinese or English. English manuscripts should follow Springer LNCS Authors Instructions. Accepted English submissions will be published in by Springer in the Communications in Computer and Information Science series. Chinese manuscripts should follow the format of Journal of Xiamen University (Natural Science). Accepted Chinese submissions will be published separately in Journal of Xiamen University (Natural Science) or Journal of Jiangxi Normal University (Natural Science). Selected excellent Chinese submissions will be recommended to the SCIENCE CHINA, the Journal of Software, the Acta Automatica Sinica or the Journal of Chinese Information Processing.
All submissions will be reviewed double-blindly. The papers submitted for review must not contain authors' names and affiliations. Furthermore, self-references that reveal the author's identity, for example, "We showed (Authors’ name, 2018) ...", must be avoided. Instead, use citations such as "Authors’ name (2018) showed ...".