On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Delta LogNormal theory for the generation and modeling of cursive characters
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
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IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Generation of Handwritten Characters with Bayesian network based On-line Handwriting Recognizers
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Automatic Generation of Artistic Chinese Calligraphy
IEEE Intelligent Systems
Improving naturalness in text-to-speech synthesis using natural glottal source
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
Introduction to Linear Regression Analysis, Solutions Manual (Wiley Series in Probability and Statistics)
Style-preserving English handwriting synthesis
Pattern Recognition
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In this paper, we define the naturalness of handwritten characters as being the difference between the strokes of the handwritten characters and the archetypal fonts on which they are based. With this definition, we mathematically analyze the relationship between the font and its naturalness using canonical correlation analysis (CCA), multiple linear regression analysis, feedforward neural networks (FFNNs) with sliding windows, and recurrent neural networks (RNNs). This analysis reveals that certain properties of font character strokes do not have a linear relationship with their naturalness. In turn, this suggests that nonlinear techniques should be used to model the naturalness, and in our investigations, we find that an RNN with a recurrent output layer performs the best among four linear and nonlinear models. These results indicate that it is possible to model naturalness, defined in our study as the difference between handwritten and archetypal font characters but more generally as the difference between the behavior of a natural system and a corresponding basic system, and that naturalness learning is a promising approach for generating handwritten characters.