A Novel Approach to On-Line Handwriting Recognition Based on Bidirectional Long Short-Term Memory Networks
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چکیده
In this paper we introduce a new connectionist approach to on-line handwriting recognition and address in particular the problem of recognizing handwritten whiteboard notes. The approach uses a bidirectional recurrent neural network with long short-term memory blocks. We use a recently introduced objective function, known as Connectionist Temporal Classification (CTC), that directly trains the network to label unsegmented sequence data. Our new system achieves a word recognition rate of 74.0%, compared with 65.4% using a previously developed HMMbased recognition system.
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تاریخ انتشار 2007