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The
Pen Computing Group at the Thomas J. Watson Research Center has
developed ThinkScribe, a writing tablet whose "smart paper"
medium enables writers to save all their handwritten notes and
drawings in their computers. Large vocabulary (40,000 words) unconstrained
handwriting recognition software, also developed at Watson can
transform the digitized text into standard ASCII characters. The
device has potential use in a number of different fields.
In
this talk, I will present a brief overview of ThinkScribe and
discuss some of the challenges faced by Pen computing in the past
and talk about how ThinkScribe addresses some of them. I will
then move on to talk about the handwriting recognition engine
that forms a key component of this device. The recognition engine
uses hidden Markov models to model individual characters. A combination
of the character models and smart search strategies result in
a real time large vocabulary handwriting recognition system. Although
the system offers a user the convenience of operation `out of
the box', i.e. without any training on the part of the user, there
is a significant improvement in accuracy when trained for an individual's
handwriting. In this talk I will also briefly talk about strategies
that we use to adapt the writer-independent models to a user's
writing style.
BIO
Dr. Jayashree Subrahmonia received a Bachelors degree in Electrical
Engineering from the Indian Institute of Techcology in Bombay,
India; and Masters in Applied Mathematics and PhD in Electrical
Engineering from Brown University in Providence, RI. She joined
IBM's Thomas J Watson Research Center in 1994 to work on large
vocabulary unconstrained online handwriting recognition and currently
manages the pen technology group focussing on handwriting recognition
and designing hardware platforms for capturing digital ink.
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