Home| Contact Us| New Journals| Browse Journals| Journal Prices| For Authors|

Print ISSN: 0974-7710
Online ISSN:
0974-7729


  About IJWA
  Aims & Scope
Editorial Board
Contact us
Current Issue
Next Issue
Previous Issue
Sample Issue
Be a Reviewer
Publisher
Subscription
 
  How To Order
  Order Online
Price Information
Request for Complimentary
Print Copy
 
  For Authors
  Guidelines for Contributors
Online Submission
Call for Papers
Author Rights
 
 
RELATED JOURNALS
Journal of Digital Information Management (JDIM)
Journal of E-Technology(JET)

 

 
International Journal of Web Applications

Construction of Viterbi Algorithm Voice Command Model for Autonomous Learning of College English
Woyou Zhang
Macau University of Science and Technology Wei Long Road, Taipa, Macau China
Abstract: This article presents a novel approach to college English autonomous learning-a voice command model based on the Viterbi algorithm. This innovative model is designed to enhance students’ English proficiency and learning outcomes in an autonomous learning environment. The article begins by outlining the context and importance of the model’s development, then delves into the key technologies utilized in its construction, such as speech recognition, the Viterbi algorithm, and feature extraction. The article concludes with a validation of the model’s effectiveness and superiority through experiments, demonstrating its ability to accurately interpret students’ voice commands and thereby improve the efficiency of college English autonomous learning.
Keywords: Esp Theory, College English, Autonomous Learning Construction of Viterbi Algorithm Voice Command Model for Autonomous Learning of College English
DOI:https://doi.org/10.6025/ijwa/2024/16/2/44-51
Full_Text   PDF 867 KB   Download:   8  times
References:


[1] Ailing, Q. (2017). A study on college English autonomous learning model based on ESP theory. Agro Food Industry Hi Tech, 28(1), 904-907.

[2] Zhang, J. (2013). The ESP instruction: A study based on the pattern of autonomous inquiry. English Language Teaching, 6(3), 12-16.

[3] Chen, J. (2016). Interactive approach to teaching ESP reading in the autonomous learning classroom—A corpus-based discourse information analysis. Foreign Language World, 6(1), 26-29.

[4] Liu, X. (2016). Research into the influence of Internet-based ESP teaching and learning model on learner autonomy. Foreign Language Research, 10(1), 12-16.

[5] Ajideh, P. (2016). Autonomous learning and metacognitive strategies essentials in ESP class. English Language Teaching, 2(1), 162.

[6] Wang, F. Y. (2015). Study on establishment of English corpus of higher vocational schools based on ESP teaching—The case of Huzhou Vocational and Technical College. Vocational & Technical Education, 2015(2), 12-16.

[7] Hüttner, J., Smit, U., Mehlmauer-Larcher, B. (2016). ESP teacher education at the interface of theory and practice: Introducing a model of mediated corpus-based genre analysis. System, 37(1), 99-109.

[8] Tandel, N. H., Prajapati, H. B., Dabhi, V. K. (2020). Voice recognition and voice comparison using machine learning techniques: A survey. In 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS) (pp. 459-465). IEEE. https://doi.org/10.1109/ICACCS48705.2020.9074184.

[9] Singh, N., Agrawal, A., Khan, R. A. (2017). Automatic speaker recognition: Current approaches and progress in last six decades. Global Journal of Enterprise Information System, 9(3), 45-52.

[10] Dong, Y. (2022). Application of artificial intelligence software based on semantic web technology in English learning and teaching. Journal of Internet Technology, 23(1), 143-152.

[11] Dizon, G., Tang, D. (2020). Intelligent personal assistants for autonomous second language learning: An investigation of Alexa. JALT CALL Journal, 16(2), 107-120.

 


Home | Aim & Scope | Editorial Board | Author Guidelines | Publisher | Subscription | Previous Issue | Contact Us |Upcoming Conferences|Sample Issues|Library Recommendation Form|

 

Copyright © 2010 dline.info