This paper proposes an automatic sentence segmentation method for ancient Chinese texts based on recurrent neural network (RNN). A bi-directional RNN structure with gated recurrent units (GRU) is implemented, and state transition probability and length penalty are employed in decoding to improve the accuracy. Experimental results show that proposed model achieves higher F1 score than traditional methods.
