Steganography Model and System for Automatic Generated Poem
Chinese ancient poetry has the characteristics of neat structure,rich emotions,and appropriate length,making it suitable as a nat-ural carrier for generative information hiding.However,due to its implicit semantics,profound meaning,and diverse styles,the automatic generation of poetry hiding is extremely challenging.With the emergence of big language generation models,the quality of poetry generation has been greatly improved,but there have been no reports on applying big language models to implicit writing in poetry generation.To this end,the BERT sentiment analysis model was introduced and combined with the Attention mechanism to design a hidden writing algorithm and model for Seq2Seq to automatically generate poetry.The corresponding hardware system and GUI interface were constructed based on PN40.Under the guidance of theme words and the constraints of rhythm/emotion/mutual information,multi-mode implicit poetry was generated and quickly output on the system.The experimental results show that the proposed model generates implicit poems with clear themes and consistent emotions.The BLEU evaluation value is as high as 44.3%,and the average accuracy of sentiment analysis is above 85%,greatly enhancing the perception and statistical concealment of implicit poems and accelerating the application of generative information steganography.
poetrylarge language modelsentiment analysisconcealabilityinformation steganography
万方数据
维普
