[2019-03-29] Dr. Khan Md. Anwarus Salam, Cinnamon, "Machine Translation using Ontology"(English Speech)

Poster:Post date:2019-03-15
Title: Machine Translation using Ontology
Date: 2019-03-29 3:40pm-5:00pm
Location: R103, CSIE
Speaker: Dr. Khan Md. Anwarus Salam, Cinnamon
Hosted by: Prof. Yun-Nung (Vivian) Chen


1. Machine Translation Research Challenges
  • Low resource language
  • Handling unknown words
2. Machine translation approaches
  • Example-Based Machine Translation: Chunk-String-Templates
  • Knowledge-Based Machine Translation: Universal Networking Language
3. Using UNL Ontology, WordNet to improve Machine Translation
4. Experience with Google Translate Community to improve Machine Translation for low-resource language
Dr. Khan is the Senior AI Researcher of Cinnamon. Before joining cinnamon he worked with IBM Research Tokyo as a research scientist, where he worked with natural language processing for robots. Before that during 2014 - 2016 he worked as a country engineering consultant for Google in Bangladesh. Khan did his research in machine translation at The University of Electro-Communications in Tokyo. He received his PhD and master’s degree in Information and Communication Engineering, as well as his B.Sc. in Computer Science from BRAC University, Dhaka in 2009.
About Cinnamon AI
Cinnamon AI is a Japanese startup established at the end of 2016. Besides the headquarter in Tokyo Japan, Cinnamon also has operation and R&D centers in the United States, Taiwan, and Vietnam, with a total of approximately 120 employees. Cinnamon’s mission is to “Extend human potential by eliminating repetitive tasks”. Our products covered multiple fields of Artificial Intelligence, such as Optical Character Recognition(OCR) and Automatic Speech Recognition (ASR). We devote ourselves to help white-collar workers tackle tedious tasks encountered in the various working scenarios. Cinnamon is the first Japanese AI startup invested by Sony, and is also selected by Forbes Magazine as one of the 25 Machine Learning startups to watch in 2018!
Last modification time:2019-03-15 AM 9:30

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