Professor Douglas Oard
, University of Maryland, will speak on 'Building Search Engines for the “Bottom Billion”
', in the famous room N101 at the Australian National University in Canberra, 11am, 11 December 2015.
This is an event in the CSIRO IR & Friends series, in conjunction with RSCS HCC & Friends.
About three quarters of a billion people are functionally
illiterate, meaning that they have no more than a very basic ability to
read or write. Modern search engines are powerful tools for much of the
world’s population, but if we are to build search engines for
illiterate and low-literacy users we will need to come at the problem
differently. I’ll begin by describing two lines of work on this problem
in the broad area known as Information and Communication Technology for
Development (variously, ICTD or ICT4D), one that seeks to leverage
visual interfaces, numeracy, and limited literacy, and a second that
seeks to leverage speech. I’ll then focus the rest of the talk on the
work that we have been doing on speech-to-speech retrieval.
The key challenge that we have sought to address is that most
illiterate and low-literacy users don’t speak any language for which we
have the sorts of highly engineered Large-Vocabulary Continuous Speech
Recognition (LVCSR) systems on which much of the recent work on speech
retrieval depends. A shared-task evaluation in MediaEval started to
tackle that challenge in 2011 using a Spoken Term Detection (STD)
evaluation. The results there were promising, showing that systems
could often recognize single terms in continuous speech based on
examples, without any foreknowledge of the language. In our work, we
have sought to build on one of these MediaEval systems to apply this STD
capability to perform ad hoc ranked retrieval (i.e., finding recorded
content that is most likely to satisfy a user’s information need).
I’ll describe the “Query by Babbling” interaction paradigm
that we have been exploring, in which we are exploring what would happen
if instead of short queries and long result sets, as is appropriate for
text, we had long queries and short result sets, perhaps a better
approach for speech.
I’ll then describe a test collection we have built using
spoken content from a voice forum site used by farmers in Gujarat, India
(speaking in Gujarati), some ranked retrieval systems that we have
evaluated using that collection, and the results that we have obtained.
I’ll finish up with a few thoughts on where the remaining
hard spots are with this technology, and what I see as next steps to
address those challenges. This is joint work with Jerome White (NYU Abu
Dhabi), Nintendra Rajput (IBM India Research Lab) and Aren Jansen (at
the time at the Johns Hopkins HLTCOE).
Oard is a Professor at the University of Maryland, College Park, with
joint appointments in the College of Information Studies (Maryland’s
iSchool) and the University of Maryland Institute for Advanced Computer
Studies (UMIACS). Dr. Oard earned his Ph.D. in Electrical Engineering
from the University of Maryland. His research interests center around
the use of emerging technologies to support information seeking by end
users. Additional information is available at http://terpconnect.umd.edu/~oard/.
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