On-Line Cursive Handwriting Recognition Using Hidden Markov Models and Statistical Grammars

The BYBLOS continuous speech recognition system is applied to on-line cursive handwriting recognition. By exploiting similarities between on-line cursive handwriting and continuous speech recognition, we can use the same base system adaptedto handwriting feature vectors instead of speech. The use of hidden Markov models obviates the need for segmentation of the handwritten script sentences before recognition. To test our system, we collected handwritten sentences using text from the ARPA Airline Travel Information Service (ATIS) and the ARPA Wall Street Journal (WSJ) corpora. In an

• Type: Conference
• Year: 1994
• Where: NAACL
• Authors: John Makhoul, Thad Starner, Richard M. Schwartz, George Chou
• Keywords: Continuous Speech Recognition, Cursive Handwriting Recognition, NAACL 1994, NAACL 2007, On-line Cursive Handwriting