Letter Model and Character Bigram based Language Model for Handwriting Recognition
First Claim
1. A computer-implemented method for recognizing user handwriting, the method comprising:
- receiving digital ink based on handwriting received from a user;
identifying words within the received digital ink;
for each identified word,identifying segments within the word that are potential characters or parts of characters;
classifying each segment to determine letters with which the segment may be associated;
determining a score for each classified segment, wherein a greater score indicates a higher probability that the segment represents the classification associated with the score;
selecting a recognition result for the word based on the determined score.
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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.
30 Citations
20 Claims
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1. A computer-implemented method for recognizing user handwriting, the method comprising:
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receiving digital ink based on handwriting received from a user; identifying words within the received digital ink; for each identified word, identifying segments within the word that are potential characters or parts of characters; classifying each segment to determine letters with which the segment may be associated; determining a score for each classified segment, wherein a greater score indicates a higher probability that the segment represents the classification associated with the score; selecting a recognition result for the word based on the determined score. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer system for recognizing user handwriting, the system comprising:
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an input device configured to receive input from a user and communicate the input as digital ink to an application; a word breaking component configured to divide the received digital ink into one or more words; an ink segmenting component configured to divide a word into one or more ink segments; a shape classifying component configured to determine one or more classifications that associate each ink segment as a part of a particular letter; a language model scoring component configured to assign a probability to each of the classifications; a recognition result component configured to produce a recognition result for each word based on the assigned probabilities. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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17. A computer-readable storage medium encoded with instructions for controlling a computer system to determine a score for a recognition alternative, by a method comprising:
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receiving a digital ink segment that makes up part of a word; adjusting a score based on output of a shape classifier for a recognition alternative of the digital ink segment; if the digital ink segment is the last segment in a letter, adjusting the score based on the probability that the letter ends in the digital ink segment; if there are more ink segments in the word, adjusting the score based on a bigram probability between the letter and a subsequent letter; and if the digital ink segment is the last segment in the word, providing the score for the recognition alternative. - View Dependent Claims (18, 19, 20)
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Specification