21st International Conference on Text, Speech and Dialogue
TSD 2018, Brno, Czech Republic, September 11–14 2018
 
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TSD 2018 Keynote Speakers

Kenneth W. Church

Thomas J. Watson Research Center
Yorktown Heights
NY USA

kwchurch@us.ibm.com
Kenneth.Ward.Church@gmail.com

Keynote topic - Minsky, Chomsky & Deep Nets

Abstract: When Minsky and Chomsky were at Harvard in the 1950s, they started out their careers questioning a number of machine learning methods that have since regained popularity. Minsky's Perceptrons was a reaction to neural nets and Chomsky's Syntactic Structures was a reaction to ngram language models. Many of their objections are being ignored and forgotten (perhaps for good reasons, and perhaps not). Future work ought to characterize what deep nets are good for (and what they aren't good for). Can we come up with a theory of generative capacity for deep nets? How much more can we generate with more layers? In practice, deep nets have been effective in vision, speech and machine translation, where (1) we have lots of data, (2) representations and scale don't matter much, and (3) nothing else has been all that effective. Conversely, deep nets are probably less appropriate when representations have been reasonably effective (e.g., symbolic calculus), or for large problems beyond finite-state complexity (e.g., sorting large lists, multiplying large matrices).

Kenneth Church's Biography

Kenneth Church has worked on many topics in computational linguistics including: web search, language modeling, text analysis, spelling correction, word-sense disambiguation, terminology, translation, lexicography, compression, speech (recognition, synthesis & diarization), OCR, as well as applications that go well beyond computational linguistics such as revenue assurance and virtual integration (using screen scraping and web crawling to integrate systems that traditionally don't talk together as well as they could such as billing and customer care). He enjoys working with large corpora such as the Associated Press newswire (1 million words per week) and even larger datasets such as telephone call detail (1-10 billion records per month) and web logs. He earned his undergraduate and graduate degrees from MIT, and has worked at AT&T, Microsoft, Hopkins and IBM. He was the president of ACL in 2012, and SIGDAT (the group that organizes EMNLP) from 1993 until 2011. He became an AT&T Fellow in 2001 and ACL Fellow in 2015.


























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