| Project/Area Number |
11480074
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | The University of Tokyo (2001)
Japan Advanced Institute of Science and Technology (1999-2000) |
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Principal Investigator |
SAGAYAMA Shigeki Graduate School of Information Science and Technology, Professor, 大学院・情報理工学系研究科, 教授 (00303321)
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| Co-Investigator(Kenkyū-buntansha) |
TABARU Tetsuya Graduate School of Information Science and Technology, Research Associate, 大学院・情報理工学系研究科, 助手 (90272393)
NAKAI Mitsuru Japan Advanced Institute of Science and Technology, Graduate School of Information Science, Research Associate, 情報科学研究科, 助手 (60283149)
SHIMODAIRA Hiroshi Japan Advanced Institute of Science and Technology, Graduate School of Information Science, Associate Professor, 情報科学研究科, 助教授 (30206239)
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| Project Period (FY) |
1999 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥10,600,000 (Direct Cost: ¥10,600,000)
Fiscal Year 2001: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2000: ¥3,200,000 (Direct Cost: ¥3,200,000)
Fiscal Year 1999: ¥6,200,000 (Direct Cost: ¥6,200,000)
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| Keywords | Online Handwriting Recognition / Cursive, Blind Writing / Continuous Speech Recognition Approach / Hidden Markov Model / Stroke-based Modeling / Hierarchical Kanji Structure Lexicon / Viterbi Algorithm / Handwritten by the Blind / 漢字データベース |
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| Research Abstract |
In this project, continuous speech recognition (CSR) approach was successfully applied to online handwriting recognition and produced enormous results. Replacing phonemes and grammar in CSR with 25 basic strokes and Kanji structure lexicon and utilizing highly advanced CSR techniques to make an efficient search in the solution space, the newly developed technology is able to recognize cursive and blind hand-written Kanji characters. By observing the velocity vector sequence of the pen movements, this technology estimates the intension of what Kanji character is being written instead of recognizing the drawn figure so that it may recognize heavily deformed characters even human can not read.
After establishing the above fundamental structure of the technology, we investigated a number of research items such as velocity-based features (comparing several feature parameters), pen pressure as a feature, stroke context-dependent modeling (considering stroke deformation caused by previous and following strokes), stroke macro model (adjacent strokes are combined to form a macro-stroke), adaptation to writers (adapting HMMs to the writer's characteristics), recognition of blind writing (written without seeing), recognizing overlapped writing (multiple characters on the same area), acceleration of recognition speed (improved search algorithm), curved strokes for numerics and Hirakana, and collection of cursive, blind writing and ones from blind people.
Utilizing the research results, our R&D proposal of "Handwritten Communication for the Blind" was approved by Ishikawa Prefecture with a support of 100 million yen. The two projects cooperated well with each other so that more than 1 million handwritten character data were collected including cursive, blind, and sight-impaired characters.
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