APPLICATIONS AND PROSPECTS OF ARTIFICIAL INTELLIGENCE IN LINGUISTIC RESEARCH

被引:0
作者
Jiang, Shaohua [1 ,2 ]
Chen, Zheng [3 ]
机构
[1] Fujian Univ Technol, Sch Humanities, Fuzhou 350118, Fujian, Peoples R China
[2] Krirk Univ, Bangkok 10220, Thailand
[3] Concord Univ Coll, Fujian Normal Univ, Fuzhou 350000, Fujian, Peoples R China
来源
3C TECNOLOGIA | 2024年 / 13卷 / 01期
关键词
Artificial intelligence; LSTM; joint vector; speech recognition; F1; value; DISCOURSE;
D O I
10.17993/3ctecno.2024.v13n1e45.57-76
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In modern linguistic research, the application of Artificial Intelligence has led the field and provided powerful tools and prospects for linguists. LSTM is used for extracting character features, joint vector representation and constructing text generation models and generating natural language text. LSTM is involved in the design of speech recognition network to process the input speech signals for generators and discriminators to improve the accuracy of speech recognition. By continuously optimizing the training objectives, the translation system will more accurately translate text from one language to another, thus facilitating cross-cultural communication. Through the application of artificial intelligence, the F1 value has been improved by 3.9% compared with the previous value, and the cumulative variance contribution rate of the five factors is more than 60%, with all subloadings reaching 0.4 or more. Artificial intelligence will promote the development of the field of linguistics, improve research efficiency and accuracy, and promote the innovation of language technology.
引用
收藏
页码:57 / 76
页数:20
相关论文
共 20 条
[1]   A Cross-linguistic Analysis of Formulaic Language and Meta-discourse in Linguistics Research Articles by Natives and Arabs: Modeling Saudis and Egyptians [J].
Abdulaal, Mohammad Awad Al-Dawoody .
ARAB WORLD ENGLISH JOURNAL, 2020, 11 (03) :193-211
[2]  
Bernardo M. L. P., 2022, Teaching Literature in Translation: Pedagogical Contexts and Reading Practices, P262
[4]   Birdsong Learning and Culture: Analogies with Human Spoken Language [J].
Bruno, Julia Hyland ;
Jarvis, Erich D. ;
Liberman, Mark ;
Tchernichovski, Ofer .
ANNUAL REVIEW OF LINGUISTICS, VOL 7, 2021, 7 :449-472
[5]  
Budinsky R., 2023, The Journal of the Acoustical Society of America
[6]   Surprise markers in applied linguistics research articles: A diachronic perspective [J].
Chen, Lang ;
Hu, Guangwei .
LINGUA, 2020, 248
[7]   Mini-batch sample selection strategies for deep learning based speech recognition [J].
Dokuz, Yesim ;
Tufekci, Zekeriya .
APPLIED ACOUSTICS, 2021, 171
[8]  
Hamzah M. H., 2022, Journal of Language and Linguistic Studies, V18, P1270
[9]   Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching [J].
Hou, Wenxin ;
Wang, Jindong ;
Tan, Xu ;
Qin, Tao ;
Shinozaki, Takahiro .
INTERSPEECH 2021, 2021, :3425-3429
[10]  
Ikromdjonovna K. N., 2023, J SURV FISH SCI, V10, P2127