Handwriting Recognition
To recognize the written items, we use an online handwriting
recognition system similar to the one used in the Apple Newton
[19] but using an extended feature set similar to the NPen++
recognizer [27]. In online handwriting recognition, the input to
the system is a trajectory of (x,y) coordinates over time t. The
handwriting recognition engine used was built for normal online
handwriting data aiming to recognize stylus input and writing
with a finger on a touchscreen. Its recognition accuracy is comparable
with other state-of-the-art online handwriting recognition
systems. Note that in contrast with other systems (e.g., 8000
words in [14], 13 gestures in [17]), the handwriting recognition
system is an open vocabulary recognizer that can recognize any
word that can be written with its alphabet independently of
whether it is a proper word and whether the system has ever
seen it in the past. To evaluate this, we tried to write the authors’
last names and found this to be easily possible.
Above we mentioned that GyroPen does not handle penup
movements explicitly but considers them to be part of the
writing motion. To handle such strokes, the online handwriting
recognition literature has been using pen-up strokes as part of
the observation [27]. Pen-up strokes also have been used as
a means to make models for Chinese handwriting recognition
invariant to printed and cursive writing styles [28].
The handwriting recognition system performs size and
writing-speed normalization, and therefore, the writing size and
speed of a particular item have no impact on the recognition.