TY  - CONF
AU  - Volkmar Frinken
AU  - Markus Baumgartner
AU  - Andreas Fischer
AU  - Horst Bunke
A2  - ICFHR
PY  - 2012//
TI  - Semi-Supervised Learning for Cursive Handwriting Recognition using Keyword Spotting
BT  - 13th International Conference on Frontiers in Handwriting Recognition
SP  - 49
EP  - 54
N2  - State-of-the-art handwriting recognition systems are learning-based systems that require large sets of training data. The creation of training data, and consequently the creation of a well-performing recognition system, requires therefore a substantial amount of human work. This can be reduced with semi-supervised learning, which uses unlabeled text lines for training as well. Current approaches estimate the correct transcription of the unlabeled data via handwriting recognition which is not only extremely demanding as far as computational costs are concerned but also requires a good model of the target language. In this paper, we propose a different approach that makes use of keyword spotting, which is significantly faster and does not need any language model. In a set of experiments we demonstrate its superiority over existing approaches.
SN  - 10.1109/ICFHR.2012.268
SN  - 978-1-4673-2262-1
L1  - http://refbase.cvc.uab.es/files/FBF2012.pdf
N1  - DAG
ID  - Volkmar Frinken2012
ER  -