Research on natural language generation and text composition based on deep learning and text generation

Bingchen He; Xiaohan Wang

doi:10.1117/12.3025850

8 April 2024 Research on natural language generation and text composition based on deep learning and text generation

Bingchen He, Xiaohan Wang

Proceedings Volume 13090, International Conference on Computer Application and Information Security (ICCAIS 2023); 130901C (2024) https://doi.org/10.1117/12.3025850
Event: International Conference on Computer Application and Information Security (ICCAIS 2023), 2023, Wuhan, China

Abstract

The rapid development of deep learning technology has significantly impacted the fields of Natural Language Generation (NLG) and text composition, leading to numerous noteworthy advancements. These advancements encompass innovations in language models, sequence-to-sequence generation, automatic summarization, automated document generation, and content creation. This paper analyzes the natural language generation and text composition processes within the context of deep learning and text generation, focusing on language models, sequence-to-sequence generation, automatic summarization, automated document generation, and content creation. The application of deep learning models in text generation is exemplified by the construction of a Seq2Seq model based on a Bi-LSTM network architecture, employing a greedy algorithm to achieve rapid text generation.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bingchen He and Xiaohan Wang "Research on natural language generation and text composition based on deep learning and text generation", Proc. SPIE 13090, International Conference on Computer Application and Information Security (ICCAIS 2023), 130901C (8 April 2024); https://doi.org/10.1117/12.3025850

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