Resurrecting Ancient Languages
Scientists Create Automated 'Time Machine' to Reconstruct Ancient Languages.
Ancient languages hold a treasure trove of information about the culture, politics and commerce of millennia past. Yet, reconstructing them to reveal clues into human history can require decades of painstaking work. Now, scientists at the University of California, Berkeley, have created an automated "time machine," of sorts, that will greatly accelerate and improve the process of reconstructing hundreds of ancestral languages. In a compelling example of how "big data" and machine learning are beginning to make a significant impact on all facets of knowledge, researchers from UC Berkeley and the University of British Columbia have created a computer program that can rapidly reconstruct "proto-languages" -- the linguistic ancestors from which all modern languages have evolved. These earliest-known languages include Proto-Indo-European, Proto-Afroasiatic and, in this case, Proto-Austronesian, which gave rise to languages spoken in Southeast Asia, parts of continental Asia, Australasia and the Pacific.
The research team's computational model uses probabilistic reasoning -- which explores logic and statistics to predict an outcome -- to reconstruct more than 600 Proto-Austronesian languages from an existing database of more than 140,000 words, replicating with 85 percent accuracy what linguists had done manually. While manual reconstruction is a meticulous process that can take years, this system can perform a large-scale reconstruction in a matter of days or even hours, researchers said. Not only will this program speed up the ability of linguists to rebuild the world's proto-languages on a large scale, boosting our understanding of ancient civilizations based on their vocabularies, but it can also provide clues to how languages might change years from now. "Our statistical model can be used to answer scientific questions about languages over time, not only to make inferences about the past, but also to extrapolate how language might change in the future," said Tom Griffiths, associate professor of psychology, director of UC Berkeley's Computational Cognitive Science Lab.
The discovery advances UC Berkeley's mission to make sense of big data and to use new technology to document and maintain endangered languages as critical resources for preserving cultures and knowledge.
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