Modeling English vocabulary acquisition through the biomechanics of speech and Large Language Models

被引:0
作者
Shang, Jingya [1 ]
机构
[1] School of Foreign Languages, Zhongyuan Institute of Science and Technology, Zhengzhou
来源
MCB Molecular and Cellular Biomechanics | 2025年 / 22卷 / 01期
关键词
age-related learning; articulatory phonetics; Large Language Models; motor control; speech biomechanics; speech production; vocabulary acquisition;
D O I
10.62617/mcb699
中图分类号
学科分类号
摘要
This study investigates the relationship between biomechanical constraints in speech production and English vocabulary acquisition by integrating Large Language Models (LLMs). Using a sample of 51 Mandarin Chinese speakers in Shenzhen, China, divided into three age groups (children: 8-12 years, adolescents: 13-17 years, and adults: 18-25 years), we conducted a 12-week longitudinal study combining articulatory measurements with computational analysis. The research employed electromagnetic articulography, surface electromyography, and advanced language modeling to examine speech patterns and learning outcomes. Results reveal significant age-related differences in articulatory kinematics, with children showing larger tongue displacements (14.3 ± 2.1 mm) and higher muscle activation levels than adults. Integrating biomechanical constraints into LLM analysis improved prediction accuracy by 18.7% for children and 14.2% for adults, though at the cost of increased computational resources. Strong negative correlations were found between articulatory effort and learning success (r = -0.824 for children, p < 0.001), with retention rates significantly influenced by motor complexity. These findings suggest that biomechanical factors play a crucial role in vocabulary acquisition, particularly in younger learners, and that incorporating these constraints into computational models can enhance our understanding of language learning processes. This integrated approach offers new insights for developing age-appropriate language teaching methodologies and improving predictive models for learning outcomes. © 2025 by author(s).
引用
收藏
相关论文
共 33 条
[1]  
Hummel K. M., Introducing second language acquisition: Perspectives and practices, (2021)
[2]  
Uy F., Cojuangco F., Canes R. M., Kilag O. K., Abendan C. F., Dicdiquin I., Syntax and Beyond Investigating Chomsky's Universal Grammar in the Acquisition of Second Languages, Excellencia: International Multi-disciplinary Journal of Education (2994-9521), 1, 5, pp. 345-357, (2023)
[3]  
SWARGIARY K., Language and Learning: The Crucial Role of Language in the Teaching-Learning Process, (2024)
[4]  
Grishechko E. G., Language and cognition behind simile construction: A Python-powered corpus research, TLC Journal, 7, 2, (2023)
[5]  
Ciccarelli M., Papetti A., Germani M., Exploring how new industrial paradigms affect the workforce: A literature review of Operator 4.0, Journal of Manufacturing Systems, 70, pp. 464-483, (2023)
[6]  
Maassen B., Terband H., Toward process-oriented, dimensional approaches for diagnosis and treatment of speech sound disorders in children: Position statement and future perspectives, Journal of Speech, Language, and Hearing Research, pp. 1-22, (2024)
[7]  
Xi Z., Chen W., Guo X., He W., Ding Y., Hong B., Gui T., The rise and potential of large language model based agents: A survey, (2023)
[8]  
Ovy E. G., Romanyk D. L., Flores Mir C., Westover L., Modeling and evaluating periodontal ligament mechanical behaviour and properties: A scoping review of current approaches and limitations, Orthodontics & Craniofacial Research, 25, 2, pp. 199-211, (2022)
[9]  
Skinner B. F., Verbal behavior, (1957)
[10]  
Chomsky N., Review of Verbal Behavior by B.F. Skinner, Language, 35, 1, pp. 26-58, (1959)