Substroke Approach to HMM-based On-line Kanji Handwriting Recognition
Autor: | N. Akira, Shigeki Sagayama, Mitsuru Nakai, Hiroshi Shimodaira |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2001 |
Předmět: |
Kanji
Grammar business.industry Character (computing) Computer science Speech recognition media_common.quotation_subject computer.software_genre ComputingMethodologies_PATTERNRECOGNITION Handwriting recognition Japanese Artificial intelligence Line (text file) business Hidden Markov model computer Sentence Natural language processing media_common |
Zdroj: | ICDAR |
Popis: | A new method is proposed for on-line handwriting recognition of Kanji characters. The method employs substroke HMMs 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 HMMs, a character structure dictionary and a decoder. The present approach has the following advantages over the conventional methods that employ whole character HMMs. 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. |
Databáze: | OpenAIRE |
Externí odkaz: |