TY - GEN
T1 - Research on acrostic poem generation based on handwritten Chinese character recognition and machine learning
AU - Li, Yanjun
AU - Jia, Huiran
AU - Li, Yuan
AU - Wang, Qinglin
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/6
Y1 - 2020/11/6
N2 - In this paper, we study the automatic generation of acrostic poems based on handwritten Chinese character recognition and machine learning. First, AlexNet network and ResNet50 network are used to train the handwritten Chinese character data set respectively. Select ResNet50 which recognition accuracy is 82.56% as the input module of poem generation model. After this, the GPT-2 model is used to train 26,000 five-character poems in order to build an acrostic poem generation model. Finally, combine these two parts. If we input four images of handwritten Chinese characters, the system can automatically generate a fluent acrostic poem headed by these four characters after character recognition. Experiment results verify the effectiveness of the method.
AB - In this paper, we study the automatic generation of acrostic poems based on handwritten Chinese character recognition and machine learning. First, AlexNet network and ResNet50 network are used to train the handwritten Chinese character data set respectively. Select ResNet50 which recognition accuracy is 82.56% as the input module of poem generation model. After this, the GPT-2 model is used to train 26,000 five-character poems in order to build an acrostic poem generation model. Finally, combine these two parts. If we input four images of handwritten Chinese characters, the system can automatically generate a fluent acrostic poem headed by these four characters after character recognition. Experiment results verify the effectiveness of the method.
KW - acrostic poem generation
KW - handwritten Chinese character recognition
KW - machine learning
KW - neural network
UR - http://www.scopus.com/inward/record.url?scp=85100925535&partnerID=8YFLogxK
U2 - 10.1109/CAC51589.2020.9327699
DO - 10.1109/CAC51589.2020.9327699
M3 - Conference contribution
AN - SCOPUS:85100925535
T3 - Proceedings - 2020 Chinese Automation Congress, CAC 2020
SP - 1287
EP - 1292
BT - Proceedings - 2020 Chinese Automation Congress, CAC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Chinese Automation Congress, CAC 2020
Y2 - 6 November 2020 through 8 November 2020
ER -