Letter model and character bigram based language model for handwriting recognition
US8559723B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 29, 2008 |
| Grant date | Oct 15, 2013 |
| Priority date | — |
| Expiry date | Jan 21, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A handwriting recognition system is described that includes a language model with scoring to improve recognition accuracy, such as for words outside of a selected language model. The handwriting recognition system increases the accuracy of handwriting recognizers that perform segmentation of ink into atomic elements (segments) and then classify each ink segment separately. After segmentation, a shape classifier estimates the class (letter) probabilities for each segment of ink by producing a corresponding score. The system applies the language model scoring to the shape classification results and typically selects the class with the highest score as the recognition result. Because the language model is not too restrictive, it works well for recognizing any word, even those that would not be in a dictionary for the current language. Thus, the handwriting recognition system produces better recognition results and can often recognize words that dictionary-based language models would not recognize correctly.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.