About
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How can we document detailed data about all the world's language in a consistent, unified source, in a way that can serve knowledge and technology needs for people and their machines around the globe? Dictionaries have historically presented selective information about words and their meanings within a language, or translation equivalents between languages, in idiosyncratic, incommensurable formats with little basis in data science. The Kamusi Project introduces a new approach, conceiving of language as a matrix of interrelated data elements. By documenting these elements within each language, and linking elements at conceptual and functional nodes across languages, Kamusi aims toward an elusive Big Data goal: "every word in every language." If successful, the results will run the gamut from preserving the human heritage embedded in endangered languages, to providing international vocabularies for students to succeed in science, to a Star Trek-like universal translator embedded in your smart watch. In this talk, the project's founder discusses the nefarious complexities working against the creation of a universal language data platform, and the systems Kamusi has designed to collect, codify, and deploy quantum-level linguistic data within one massive global dictionary.
Bio: Martin Benjamin is the founder and director of the Kamusi Project (http://kamusi.org), an international non-profit dedicated to producing dictionary and learning resources for languages worldwide. Now resident in Lausanne, he was born and raised in the United States. His PhD in Anthropology, from Yale University, examined international aid in rural Tanzania. He is a senior scientist at the Distributed Information Systems Laboratory (LSIR) at EPFL, where he is developing methods to assemble reliable data across languages. .
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The talk
Credits and licence
- Institution
- CERN
- Department
- White Area Meetings
- Speaker
- Martin Dr. Benjamin
- Year
- 2015
- Language
- English
- Subjects
- Astronomy and space, Languages and linguistics
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed