With National Science Foundation support, Dr. Joseph E. Grimes will conduct two years of linguistic research to extend the capabilities of comparative linguists by matching their expertise in making pattern recognition judgments with a computational tool that organizes all their data in response to those judgments. This division of labor will allow linguists to stay on top of greater quantities of data from more speech varieties than has ever been possible, because it provides an information technology infrastructure for their discipline. Though notable work in language comparison has been done by hand, it consumes years; indeed, for much of the world there are more educated guesses about what the linguistic relationships might be than there is well-martialed evidence for those relationships. This project's linguist-machine partnership will empower investigators to do their analysis expeditiously (including adding in data from languages that could become extinct in the next generation and be lost to science), to follow out competing hypotheses, to work collegially as easily as individually, and to offer precise documentation to others through public archives. All these things have been difficult to do using traditional methods.
To find out how human groups have diverged and migrated scholars must draw not only on written and oral history, but also on recoverable prehistory, which is accessible mostly through comparative linguistics, archeology, and genetics. If linguists are enabled to fill the gaps in their data and to make more precise their reconstructions of what our ancestral languages must have been like, it will lead to better insight into the processes by which all languages (including English) change over time, and to better understanding of connections between ancestral languages and ancient culture patterns. Seeing language history in this way also adds the time dimension to our understanding of humanity's capacity for language, and helps us to value language diversity rather than deplore it. Solid research in this area, which the proposed tool will promote, can also help traditional societies to become aware of a deeper heritage than what their oral history alone gives them. On a more immediate scale, it can identify areas where educational materials and literature developed in one of a closely related group of languages that share a common culture can be easily morphed into preliminary drafts of those materials for other languages in the same group.
