EECS500 Fall 2017 Department Colloquium

Michael White
Ambiguity Avoidance in Natural Language Generation: Steering Clear of "Vicious" Ambiguities and Crowdsourcing Clarifications for Parser Training
Ohio State University
White 411
1:30 - 2:30 PM
October 6, 2017

In this talk, I will discuss two scenarios where it is important to
avoid generating sentences with structural ambiguities.  In the first
part of the talk, I will investigate whether statistical parsers can
be used for self-monitoring in natural language generation in order to
avoid so-called "vicious" ambiguities, namely those where the intended
interpretation fails to be considerably more likely than alternative
ones.  In this part of the talk, I will demonstrate that although
using statistical parsers for this purpose is more difficult than one
might expect---since automatic parsers too often make errors that
human readers would be unlikely to make---by training a ranking model
using features from the generator together with multiple parsers,
successful self-monitoring can be achieved.  In the second part of the
talk, I will investigate whether natural language generation can be
used to automatically construct disambiguating paraphrases for
structurally ambiguous sentences---that is, paraphrases that clarify
the competing interpretations of a structurally ambiguous
sentence. Here I will present an experiment which suggests that by
simply asking naive annotators to clarify which paraphrase is closer
in meaning to the original sentence, the resulting paraphrases can
potentially enable meaning judgments for parser training and domain
adaptation to be crowd-sourced on a massive scale.


Dr. Michael White is an Associate Professor in the Department of
Linguistics at The Ohio State University.  After obtaining his
Ph.D. in Computer and Information Science from the University of
Pennsylvania in 1994, Dr. White worked for eight years at CoGenTex,
Inc., where he focused on developing practical applications of natural
language generation technologies during multiple SBIR and DARPA
projects and industrial consulting engagements.  In 2002, Dr. White
crossed the pond to Scotland where he worked for three years as a
Research Fellow at the University of Edinburgh, managing Edinburgh's
effort on the COMIC dialogue system project as part of the EU's Fifth
Framework Programme.  During this time, Dr. White also took over the
development of the open source OpenCCG library, the first practical
system for parsing and realization with Combinatory Categorial
Grammar.  With his colleagues in Edinburgh, Dr. White developed
grammar-based and data-driven methods for producing utterances that
use prosody to help highlight trade-offs among the available options
that are important to a user.  Since joining the faculty at OSU in
2005, Dr. White has continued to develop OpenCCG, extending it to a
broad-coverage setting, supported by multiple NSF grants.  He has also
become interested in applications of grammar-based paraphrasing,
including for data augmentation in the context of OSU's virtual
patient dialogue system.