Hidden markov model based handwriting/calligraphy generation
AssigneeMicrosoft Corporation
InventorsPeng Liu, Yi-Jian Wu, Lei Ma, Frank Kao-PingK Soong
Life of this patent
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Abstract
An exemplary method for handwritten character generation includes receiving one or more characters and, for the one or more received characters, generating handwritten characters using Hidden Markov Models trained for generating handwritten characters. In such a method the trained Hidden Markov Models can be adapted using a technique such as a maximum a posterior technique, a maximum likelihood linear regression technique or an Eigen-space technique.
Claims19
A method for handwritten character generation, implemented at least in part by a computing device, the method comprising:
- receiving a character;
- and
- generating a corresponding handwritten character using Hidden Markov Models trained to generate handwritten characters, the generating including using a Multi-Space Probability Distribution technique that includes a probability for determining whether a stroke is real or imaginary.
A method for adapting trained Hidden Markov Models for generation of handwritten characters, implemented at least in part by a computing device, the method comprising:
- providing initial, trained Hidden Markov Models for generation of handwritten characters;
- providing training ink data to adapt the initial, trained Hidden Markov Models;
- applying an adaptation technique to adapt the initial, trained Hidden Markov Models to the training ink data, the adaptation technique including a technique selected from a group of maximum a posterior techniques, maximum likelihood linear regression techniques and Eigen-space techniques;
- and
- rendering the generated handwritten characters using a pen model, the pen model including a plurality of pen parameters.
A computing device for generating handwritten characters, the device comprising:
- a processor;
- a user input mechanism;
- a display;
- control logic implemented at least in part by the processor to generate handwritten characters based on an algorithm that uses Hidden Markov Models;
- and
- a pen model implemented at least in part by the processor to render the generated handwritten characters based at least in part on a probability for determining whether a particular stroke is real or imaginary, the pen model comprising pen parameters.
Dependencies are inferred from the claim text.