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A CTC output layer contains as many units as there are labels in the task, plus an additional “blank” or “no label” unit. 11) ykt = t , k exp (uk ) where utk is the unsquashed activation of output unit k at time t, and ykt is the activation of the same unit after the softmax function is applied. 13) t=1 where πt is the label observed at time step t along path π. Implicit in the above equation is the assumption that the network outputs are conditionally independent at different times, given the internal state of the network.
The third essential design parameter is the number of models to be trained. If the alphabet is not too large, one HMM can be trained for each character or digit. Otherwise, the characters can be split into graphemes, which are shared among several characters, and one HMM can be trained for each grapheme. In the application of handwritten word recognition there exist two strategies for choosing the HMMs. Under the first strategy one HMM is trained for each word in the dictionary. This strategy fails if there is a large number of words in the dictionary, because in this case there is not a sufficiently large amount of training data for each HMM.
2003)] a system for extracting text from documents written on a tablet PC has been presented. This system uses the time stamps to derive an initial guess about the text line locations, and groups the lines and blocks afterwards. Then a set of local and global features is extracted and classified using a decision tree. , drawings, text, and gestures, in an interactive pen-based system. A system that distinguishes between three modes (drawing, text, and gesture) has been presented in [Rossignol et al.
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