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Content Provider | IEEE Xplore Digital Library |
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Author | Nakai, M. Akira, N. Shimodaira, H. Sagayama, S. |
Copyright Year | 2001 |
Description | Author affiliation: Graduate Sch. of Inf. Sci., Japan Adv. Inst. of Sci. & Technol., Japan (Nakai, M.) |
Abstract | A new method is proposed for online handwriting recognition of Kanji characters. The method employs substroke HMM as minimum units to constitute Japanese Kanji characters and utilizes the direction of pen motion. The main motivation is to fully utilize the continuous speech recognition algorithm by relating sentence speech to Kanji character phonemes to substrokes, and grammar to Kanji structure. The proposed system consists input feature analysis, substroke HMM, a character structure dictionary and a decoder. The present approach has the following advantages over the conventional methods that employ whole character HMM. 1) Much smaller memory requirement for dictionary and models. 2) Fast recognition by employing efficient substroke network search. 3) Capability of recognizing characters not included in the training data if defined as a sequence of substrokes in the dictionary. 4) Capability of recognizing characters written by various different stroke orders with multiple definitions per one character in the dictionary. 5) Easiness in HMM adaptation to the user with a few sample character data. |
Sponsorship | IAPR |
Starting Page | 491 |
Ending Page | 495 |
File Size | 456434 |
Page Count | 5 |
File Format | |
ISBN | 0769512631 |
DOI | 10.1109/ICDAR.2001.953838 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2001-09-13 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Hidden Markov models Handwriting recognition Character recognition Speech recognition Dictionaries Information science Training data Decoding Personal digital assistants Writing |
Content Type | Text |
Resource Type | Article |
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