Handwriting recognition systems and methods
The present disclosure includes systems and methods for handwriting recognition. Handwriting data is received. Geometric data of text in handwriting data is determined. Sub-characters of the text are determined. Sub-characters of text are matched to a model. Most probable characters of the text is determined based on the matching.
1. A method for recognizing handwriting, the method comprising:
receiving handwriting data;
determining geometric data of text in handwriting data;
determining sub-characters of the text;
matching sub-characters of text to a model; and
determining most probable characters of the text based on said matching,
wherein the model includes co-articulation of every pair of characters to make use of their orthographic evidence to reduce their variance.
2. The method of claim 1 , further comprising estimating math support to reduce variance of segments of the segmentation of the sub-characters of the text.
3. A non-transitory computer-readable storage medium storing instructions for handwriting recognition, the instructions when executed by one or more processors causing the one or more processors to perform steps comprising:
receiving handwriting data;
determining geometric data of text in handwriting data;
determining sub-characters of the text;
matching sub-characters of text to a model; and
determining most probable characters of the text based on said matching,
wherein the model includes co-articulation of every pair of characters to make use of their orthographic evidence to reduce their variance.
4. A computer system for handwriting recognition, the computer system comprising: one or more computer processors; and one or more non-transitory computer-readable storage media, the storage media storing computer program instructions executable by the one or more computer processors to perform steps comprising:
receiving handwriting data;
determining geometric data of text in handwriting data;
determining sub-characters of the text;
matching sub-characters of text to a model; and
determining most probable characters of the text based on said matching,
wherein the model includes co-articulation of every pair of characters to make use of their orthographic evidence to reduce their variance.
5. The method of claim 3 , further comprising using arc lengths of segments of the sub-characters of the text.