Online handwriting recognition: the NPen++ recognizer |
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Authors: | S Jaeger S Manke J Reichert A Waibel |
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Affiliation: | (1) Interactive Systems Laboratories, University of Karlsruhe, Computer Science Department, 76128 Karlsruhe, Germany; e-mail: stefan.jaegar@ira.uka.de , DE;(2) Interactive Systems Laboratories, Carnegie Mellon University, School of Computer Science, Pittsburgh, PA 15213-3890, USA , US |
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Abstract: | This paper presents the online handwriting recognition system NPen++ developed at the University of Karlsruhe and Carnegie
Mellon University. The NPen++ recognition engine is based on a multi-state time delay neural network and yields recognition
rates from 96% for a 5,000 word dictionary to 93.4% on a 20,000 word dictionary and 91.2% for a 50,000 word dictionary. The
proposed tree search and pruning technique reduces the search space considerably without losing too much recognition performance
compared to an exhaustive search. This enables the NPen++ recognizer to be run in real-time with large dictionaries. Initial
recognition rates for whole sentences are promising and show that the MS-TDNN architecture is suited to recognizing handwritten
data ranging from single characters to whole sentences.
Received September 3, 2000 / Revised October 9, 2000 |
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Keywords: | : Online handwriting recognition – Neural networks – Pen-based computing – Pattern recognition – Human-computer interaction |
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