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Text steganography on RNN-Generated lyrics

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成果类型:
期刊论文
作者:
Tong, Yongju;Liu, YuLing*;Wang, Jie;Xin, Guojiang
通讯作者:
Liu, YuLing
作者机构:
[Tong, Yongju; Liu, YuLing] Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Hunan, Peoples R China
[Wang, Jie] Univ Massachusetts Lowell, Dept Comp Sci, Lowell, MA 01854 USA
[Xin, Guojiang] Hunan Univ Chinese Med, Coll Management & Informat Engn, Changsha 410208, Hunan, Peoples R China
通讯机构:
[Liu, YuLing] H
Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Hunan, Peoples R China.
语种:
英文
关键词:
text steganography;lyric generation;recurrent neural networks;Char-RNN;Word-RNN
期刊:
Mathematical Biosciences and Engineering
ISSN:
1547-1063
年:
2019
卷:
16
期:
5
页码:
5451-5463
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61872134, 61502242]; Natural Science Foundation of Hunan ProvinceNatural Science Foundation of Hunan Province [2018JJ2062, 2018JJ2301]; National Key Research and Development Program [2017YFC1703306]; Hunan Provincial 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property [2017TP1025]
机构署名:
本校为其他机构
院系归属:
信息科学与工程学院
摘要:
We present a Recurrent Neural Network (RNN) Encoder-Decoder model to generate Chinese pop music lyrics to hide secret information. In particular, on a given initial line of a lyric, we use the LSTM model to generate the next Chinese character or word to form a new line. In so doing, we generate the entire lyric from what has been generated so far. Using common lyric formats and rhymes we extracted, we generate lyrics embedded with secret information to meet the visual and pronunciation requirements. We carry out experiments and theoretical analysis, and show that lyrics generated by our method...

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