Philip Resnik
Philip Resnik
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Machine translation.
My recent work has largely been focused on machine translation and
multilingual natural language processing, exploiting
parallel corpora and linguistically informed
modeling in statistical machine translation and in multilingual
natural language processing more generally (with a focus on Chinese
and Arabic, as well as other less-studied languages). As part of this
effort, my postdoc David
Chiang (now at USC/ISI) developed
Hiero,
the first syntax-based system to demonstrate performance comparable to
then state-of-the-art statistical phrase-based MT systems (see 2005
NIST MT Evaluation results). I have worked with a number of
students to further improve hierarchical phrase-based translation, and
some innovations include the introduction of lattice
decoding (useful in translation of speech recognition output and also
for text translation of morphologically complex languages),
development of efficient algorithms for using suffix array
representations in hierarchical decoding, use of
English-to-English translation to create artificial reference
translations for use in parameter tuning, the introduction of soft syntactic
constraints based on source language structure, and exploitation of
lattices and forests to represent source language paraphrase and
syntactically driven reordering alternatives.
Crowdsourcing and translation.
Connected with my machine translation research, Ben Bederson and I
have been working on an ambitious attempt to achieve low cost, high quality translation by taking advantage of
monolingual human participants in a computer-assisted translation protocol, in a project we call
"Translation as a Collaborative Process". We're blending ideas from machine translation, human computer-interfaces, and
distributed human computation ("crowdsourcing"), and tackling the real-world problem of translating books
in the International Children's Digital Library. We received a
2009 Google Research Award sponsoring
this work, as well as funding from NSF. In September 2009, Ben gave a
Google tech talk about the project which is available on YouTube.
Ben and I now have a follow-up Google Research Award in which we're collaborating with Chris
Callison-Burch to bring his crowdsourcing work and ours together in a framework we're calling "Translate the World".
Clinical informatics. Since about 1999 I've been involved in natural language
processing for clinical documentation. I helped start up CodeRyte, Inc.,
which became the nation's fastest growing provider of NLP solutions in healthcare (see, e.g.,
Deloitte's Technology
Fast 500 and
the Inc. 5000
listings) and was acquired in April 2012
by 3M
Health Information Systems. I developed major pieces of the core
technology, helped build an excellent language technology team, and I
continue to advise on technology development and strategic
direction.
Somewhere along the way, much to my surprise, I was listed at #82 on the Future Health 100, a list of
"the most creative and influential innovators working in healthcare today"
at healthspottr.com.
Computational psycholinguistics.
During the next several years, I hope to re-engage more fully with my
interests in computational psycholinguistics. I'm particularly
interested in the possibility that ideas from (statistical)
information theory may have a useful role to play in explaining why
language works the way it does. (This is an idea I first began
exploring in my dissertation [ps,
pdf], back in 1993, and in
recent years a variety of people like John Hale, Roger Levy, and
Florian Jaeger, among others, have done very interesting work in the
same spirit.) I'm also interested in using Bayesian modeling as a way
to bring linguists here with cognitive modeling interests together
with computational linguists focusing on applications. Momentum for
that around here has already started building with the recent arrival
of Naomi Feldman in our Linguistics Department.
Empirical linguistics.
I'm quite interested in promoting the use of naturally occurring data as evidence
in linguistics research. I led the development of the Linguist's Search Engine, a tool
designed to make it easier for linguists to search naturally occurring
data using syntactic and lexical criteria. This tool was intended to
make it easier for more linguists to go beyond the exclusive use of
introspective judgments as empirical evidence, which can lead to useful and interesting
results. In follow-on work with the Center for the Advanced Study of
Language (CASL), we ported the LSE to Chinese, and the LSE code is
available under an open source license. (Aaron Elkiss was the LSE's
chief architect, implementor, and guru. I kept it running for a number of years
after he graduated, but eventually retired it. Anyone interested in
resurrecting it: the source code is available.)
See my on-line list of publications for links
to papers on the above research topics and more.
Research Interests
Computational social science. I have been doing
work on sentiment analysis and related topics such as persuasion,
framing, and "spin", with a particular interest in the connections
among lexical semantics, surface linguistic expression, and underlying
internal state. One area in which I'm excited about applying these ideas is
computational political science. For example, why does my son say "My toy broke"
instead of "I broke my toy"? He's using syntax to package up the
statement about what happened in a way that de-emphasizes semantic
properties such as causation, volition, and change-of-state. (This is
an example of using syntax for "spin", just the same way that Ronald
Reagan did in 1987 when he sidestepped attributing responsibility for
the Iran-contra scandal; remember "Mistakes were made"? Precocious
child.) My
student Stephan
Greene
did a
fascinating dissertation on this topic, and for a
conference-paper-length description see
our 2009
NAACL paper. Current topics of investigation include modeling
syntax/semantics/sentiment connections in a Bayesian framework,
bootstrapping multilingual sentiment analysis capabilities, and
working with political scientists to model agenda setting and framing
in political discourse. I've also been working with political
scientist collaborators on
the React Labs project, a
smartphone app for large scale, real-time collection of people's
responses during live events like political debates.
Outside academia, I do real-world sentiment
analysis as Lead Scientist
with Converseon Inc., a leading
social media firm.
Professional History
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Professional Activities
The Rest
Course Information
My regular teaching schedule generally includes a seminar in the fall,
and the second half of the graduate NLP intro in the spring. Sometimes
I've also taught the first half of the graduate NLP intro. Specifics
below.
Computational Linguistics Colloquium Series
Other Links
Contact info
Philip Resnik, Professor
Department of Linguistics and Institute for Advanced Computer Studies
1401 Marie Mount Hall
University of Maryland Phone: : See below
College Park, MD 20742 USA Linguistics Fax : (301) 405-7104
http://umiacs.umd.edu/~resnik E-mail: resnik [AT] umd _DOT_ edu
UMIACS office: AV Williams 3133
By far the best way to reach me is by e-mail to resnik [AT] umd _DOT_ edu.
However, you can also use Google Voice to connect with me.
Click on the widget below, and Google Voice will call your phone to initiate a call to my phone.
Oh, and by the way, my name is not spelled Philip Resnick,
Phillip Resnik, or Phillip Resnick, though this explicit disclaimer
may help people who don't know that find this page!
