Emerging trends: A tribute to Charles Wayne

By Kenneth Ward Church. 2017

14 citations recorded by the source corpus.

Abstract Charles Wayne restarted funding in speech and language in the mid-1980s after a funding winter brought on by Pierce’s glamour-and-deceit criticisms in the ALPAC report and ‘Whither Speech Recognition’. Wayne introduced a new glamour-and-deceit-proof idea, an emphasis on evaluation. No other sort of program could have been funded at the time, at least in America. One could argue that Wayne has been so successful that the program no longer needs him to continue on. These days, shared tasks and leaderboards have become common place in speech and language (and vision and machine learning) research. That said, I am concerned that the community may not appreciate what it has got until it’s gone. Wayne has been doing much more than merely running competitions, but he did what he did in such a subtle Columbo-like way. Going forward, government funding is being eclipsed by consumer markets. Those of us with research to sell need to find more and more ways to be relevant to potential sponsors given this new world order.

Subfields: Artificial Intelligence, Natural Language Processing

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Citations in the corpus

AI and the Everything in the Whole Wide World Benchmark (2021, background): “Several linguists [e.g. Liberman, 2010, Church, 2018] have traced the inﬂuence of Fred Jelinek at IBM and Charles Wayne at DARPA as crucial protagonists in the development of a common framework for the quantitative assessment of computational linguistic tasks, notably within speech recognition and…”
Are We Learning Yet? A Meta Review of Evaluation Failures Across Machine Learning (2021, methodology): “Benchmarking was popularized in machine learning in the 1980s through the UCI dataset repository and challenges sponsored by DARPA and NIST [24, 35, 55, 81].”
Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research (2021, methodology): “The practice was originally introduced to MLR after the “AI Winter” of the 1980s by government funders, who sought to more accurately assess the value received on grants [15, 16].”