Haiku Generation Based on Motif Images Using Deep Learning Koki Yoneda 1 Soichiro Yokoyama 2 Tomohisa Yamashita 2 Hidenori Kawamura Scho

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1 Haiku Generation Based on Motif Images Using Deep Learning Koki Yoneda 1 Soichiro Yokoyama 2 Tomohisa Yamashita 2 Hidenori Kawamura School of Engineering Hokkaido University 2 2 Graduate School of Information Science and Technology, Hokkaido University Abstract:,.,,,, LSTM,,,.,LSTM 1 1.1,,.,Google Deep Convolution Neural Network (CNN) Deep CNN, Recurrent Neural Network (RNN)[3] RNN Google [4]., DCGAN, [5],,,17,, 1 [1][2], yoneda@complex.ist.hokudai.ac.jp,,,,,,, [6][8], [7] 1.2,,,,,,,,

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2 2, tanh, o t o t = σ(w o [h t 1, x t ] + b o ), h t h t = o t tanh(c t )., 2.1, (Long Short-Term Memory, LSTM ) LSTM,, 1, (Convolutional Neurak Network, CNN ),, CNN,,,., 3 3 1: LSTM, 4,,, tanh 1 x t f t = σ(w f [h t 1, x t ] + b f ) i t = σ(w i [h t 1, x t ]+b i ) tanh C C t = tanh(w C [h t 1, x t ] + b C ) i t C,C t = f t C t 1 +i t C t 3.1,, 3, web [9] [10] [11] 17, ( 38,506

3 3.2 web [12],,, 8, , imagenavi, 1,,,,, 369,754 4, 3 ID,, BPTT ID ID, 1-of-K projection layer [14] LSTM LSTM, ID 1 LSTM, LSTM LSTM TensorFlow[15] LSTM :3 LSTM :1024 :Adam[16] :0.02 :0.99 :300 :50 :100 : 2: LSTM 4.1 3, LSTM[13] 2, 3,, ID, 3: LSTM

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8 [1] [2] 2014 [3] Shujie Liu,Nan Yang,Mu Li,Ming Zhou. A Recursive Recurrent Neural Network for Statistical Machine Translation,2014,ACL. [4] Yonghui Wu, Mike Schuster, Zhifeng Chen, et al., Google s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation,2016,arXiv: [5] Alec Radford, Luke Metz, Soumith Chintala, Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks,2015,arXiv. [6] YANG, Ming, and Masafumi HAGIWARA. A Text-based Automatic Waka Generation System using Kansei. International Journal of Affective Engineering 15.2 (2016): [14] MIKOLOV, Tomas, et al. Efficient estimation of word representations in vector space. arxiv preprint arxiv: , [15] TensorFlow [16] Kingma, Diederik P., and Jimmy Ba. Adam: A method for stochastic optimization. arxiv preprint arxiv: (2014). [17] SZEGEDY, Christian, et al. Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition p [18] Levenshtein, Vladimir I. Binary codes capable of correcting deletions, insertions, and reversals. Soviet physics doklady. Vol. 10. No [7] ianchao Wu, Momo Klyen, Kazushige Ito, Zhan Chen Haiku Generation Using Deep Neural Networks 23 [8] Tosa, Naoko, Hideto Obara, and Michihiko Minoh. Hitch haiku: An interactive supporting system for composing haiku poem. International Conference on Entertainment Computing. Springer, Berlin, Heidelberg, [9] OPEN Hammerhead V1. [10] CC BY [11] [12] [13] Sundermeyer, Martin, Ralf Schlter, and Hermann Ney. LSTM neural networks for language modeling. Thirteenth Annual Conference of the International Speech Communication Association

一般社団法人電子情報通信学会 THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGIN

一般社団法人電子情報通信学会 THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS 信学技報 IEICE Technical Report SP2019-12(2019-08)