POETRY AUTOMATIC GENERATION SYSTEM BASED ON NATURAL LANGUAGE PROCESSING
POETRY AUTOMATIC GENERATION SYSTEM BASED ON NATURAL LANGUAGE PROCESSING
- Author(s): X. Xu 1 ; J. Miao 1 ; Y. Chen 1 ; S. Yang 1
- DOI: 10.1049/icp.2021.1308
For access to this article, please select a purchase option:
Buy conference paper PDF
Buy Knowledge Pack
IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.
Thank you
Your recommendation has been sent to your librarian.
- Author(s): X. Xu 1 ; J. Miao 1 ; Y. Chen 1 ; S. Yang 1
-
-
View affiliations
-
Affiliations:
1:
School of Automation, Beijing Information Science and Technology University , Beijing, 100192 , China
Source:
The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020),
2021
p.
90 – 93
-
Affiliations:
1:
School of Automation, Beijing Information Science and Technology University , Beijing, 100192 , China
- Conference: The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)
- DOI: 10.1049/icp.2021.1308
- ISBN: 978-1-83953-506-2
- Location: Online Conference
- Conference date: 28-29 November 2020
- Format: PDF
In order to increase comprehension on abstract theory and decrease the fear of writing intelligent algorithms, engineering training based on poetry automatic generation system of natural speech recognition technology is proposed. Firstly, the background of artificial intelligence(AI) is introduced, then the comprehensive experimental teaching was separated into the simple operation training model designing and exploring teaching model, due to the characteristics and problems of complex artificial intelli-gence engineering simulation education for undergraduates. Finally, Combining the advantages of some algorithms, Displaying the automatically generated poetry to collect samples, which can enable students to learn the application of intelligent algorithm intuitively. The test on the training platform shows that the automatic generation of five characters or seven characters poems has a high probability of poetic features, and the strong correlation is between the poems generated by LSTM model and keywords.
Inspec keywords: natural language processing; learning (artificial intelligence); teaching; literature; computer based training; speech processing; speech recognition
Subjects: Natural language interfaces; Computer-aided instruction; Humanities computing; Speech processing techniques