Skip to main content
SpringerLink
Log in

Application of multimedia network english listening model based on confidence learning algorithm for speech recognition

  • Original article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

Language is the most important communication tool of human beings, and listening is one of the basic skills of language expression. Without good listening comprehension ability, it is impossible to use language flexibly to communicate. Due to the influence of traditional teaching mode, Chinese students' English listening is generally poor. Therefore, a new English listening teaching mode is needed to help students improve their English listening skills. In this study, the multimedia network technology is used to realize the integrated teaching of English listening, speaking and dictation skills, and an English listening teaching model based on multimedia network and speech recognition confidence learning algorithm is proposed. First, the mainstream confidence method based on Lattice posterior probability is optimized to improve its effectiveness. Second, the obtained confidence score is converted into a discriminant confidence score by Support Vector Machine (SVM) to enhance the discriminant ability of the confidence. Finally, a score correction strategy is proposed due to the imbalance of training data. The experiment shows that the proposed teaching model of English listening based on multimedia network technology can arouse the students’ interest and improve their listening skills. And the optimized mainstream confidence method based on Lattice posteriori probability can effectively improve the recognition ability of the algorithm and the effect of English listening classes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Aoki S, Aoki Y, Bečirević D et al (2017) Review of lattice results concerning low-energy particle physics: Flavour Lattice Averaging Group (FLAG)[J]. Eur Phys J C 77(2):2890

    Article  Google Scholar 

  • Berthet C. Approximation of LRU Caches Miss Rate: Application to Power-law Popularities[J]. 2017.

  • Boţ Radu Ioan, Csetnek ER, László SC (2016) An inertial forward–backward algorithm for the minimization of the sum of two nonconvex functions. Euro J Computational Optimization 4(1):1–23

    Article  MathSciNet  MATH  Google Scholar 

  • Bransford John D, Johnson Marcia K (1972) Contextual prerequisites for understanding: Some investigations of comprehension and recall. J Verbal Learning Verbal Behav 11(6):717–726

    Article  Google Scholar 

  • Chai Z, Zhong Y, Shao Y (2021) Research on Cultivation of Academic English Ability of Non-English Majors in Applied Science and Technology Colleges-Take Changshu Institute of Technology as an example[J]. Int J Soc Sci Edu Res 4(5):77–81

    Google Scholar 

  • Chen Y, Hu S, Mao H et al (2020) Application of the best evacuation model of deep learning in the design of public structures. Image Vision Comput 102:103975

    Article  Google Scholar 

  • Chevasco D (2019) Language and Identity: How Do Different Aspects of an L2 Identity Correlate with Spoken English Ability in Japanese High School Students? [J]. J Eng Int Lang 14(1):1–19

    Google Scholar 

  • Chou HT, Johnson JT (2016) A novel acceleration algorithm for the computation of scattering from rough surfaces with the forward-backward method[J]. Radio Sci 33(5):1277–1287

    Article  Google Scholar 

  • Chouzenoux E, Pesquet JC, Repetti A (2016) A block coordinate variable metric forward–backward algorithm[J]. J Global Optim 66(3):1–29

    Article  MathSciNet  MATH  Google Scholar 

  • Davorka BačekovićMitrović, Alica Bačeković Pavelić. Multimedial characteristics od digital educational content for early reading in Croatian language[J]. 2016.

  • Erfani SM, Rajasegarar S, Karunasekera S et al (2016) High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning. Pattern Recognit 58:121–134

    Article  Google Scholar 

  • Fan T, Yan X (2020) Diagnosing English reading ability in Chinese senior high schools. StudEdu Eval 67:100931

    Article  Google Scholar 

  • Forrin ND, Groot B, Macleod CM (2016) The d-Prime Directive: Assessing Costs and Benefits in Recognition by Dissociating Mixed-List False Alarm Rates. J Exp Psychol Learn Mem Cogn 42(7):1090–1111

    Article  Google Scholar 

  • Gao X, Zhao S, C, and Shao Y, B. "An analysis of the current status and countermeasures of bike-sharing in the background of Internet." 2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS). IEEE, 2018.

  • Gillund G, Shiffrin RM (1984) A retrieval model for both recognition and recall. Psychol Rev 91(1):1

    Article  Google Scholar 

  • Girard SN, He J, Li C et al (2016) In situ nanostructure generation and evolution within a bulk thermoelectric material to reduce lattice thermal conductivity. Nano Lett 10(8):2825–2831

    Article  Google Scholar 

  • Hong HJ, El-Ganainy T, Hsu CH et al (2018) Disseminating Multi-layer Multimedia Content over Challenged Networks[J]. IEEE Trans Multimedia 99:1–1

    Google Scholar 

  • Kim S, Min D, Kim S et al (2017a) Feature Augmentation for Learning Confidence Measure in Stereo Matching[J]. IEEE Trans Image Process 99:1–1

    MathSciNet  Google Scholar 

  • Kim NH, Jung YS, Jeong WS et al (2017) Miss rate of colorectal neoplastic polyps and risk factors for missed polyps in consecutive colonoscopies. Intestinal Res 15(3):411–418

    Article  Google Scholar 

  • Mohan R, Smith JR, Li CS (2017) Adapting multimedia Internet content for universal access[J]. IEEE Trans Multimedia 1(1):104–114

    Article  Google Scholar 

  • Narayan P, Yoon J (2017) SYK-like tensor models on the lattice[J]. J High Energy Phys 2017(8):83

    Article  MathSciNet  MATH  Google Scholar 

  • Reem D, Pierro AD (2016) A new convergence analysis and perturbation resilience of some accelerated proximal forward-backward algorithms with errors. Inverse Probl 33(4):044001

    Article  MathSciNet  MATH  Google Scholar 

  • Schank RC, Korcuska M, Jona M (2016) Multimedia applications for education and training: revolution or red herring? ACM Comput Surv 27(4):633–635

    Article  Google Scholar 

  • Schönherr H, Vancso GJ (2017) Lattice Imaging of Self-Assembled Monolayers of Partially Fluorinated Disulfides and Thiols on Sputtered Gold by Atomic Force Microscopy. Langmuir 13(14):3769–3774

    Article  Google Scholar 

  • Sellamanickam S (2016) A dual coordinate descent method for large-scale linear SVM. Icml 9(3):1369–1398

    Google Scholar 

  • Shu Y (2020) Experimental Data Analysis of College English Teaching based on Computer Multimedia Technology. Comput-Aided Design Appl 17(S2):46–56

    Article  Google Scholar 

  • Srdjan Stanković, Irena Orović, Ervin Sejdić. Multimedia Signals and Systems. 2016, 716(S7):285–292.

  • Subekti AS (2019) A Study of Introduction to College English Teachers’Beliefs In Their Teaching Roles[J]. Int J Indonesian Edu Teaching (IJIET) 3(1):20–40

    Article  Google Scholar 

  • Tran TQ, Duong TM (2020) Insights into Listening Comprehension Problems: A Case Study in Vietnam. PASAA J Lang Teaching Learning Thailand 59:77–100

    Google Scholar 

  • Wang C, Lu W, Redmond SJ et al (2017) A Low-Power Fall Detector Balancing Sensitivity and False Alarm Rate. IEEE J Biomedical Health Infor 99:1

    Google Scholar 

  • Wei N, Zhang L (2017) Parameter optimization for acoustic fault samples kernel confidence measure. Acoust Soc Am J 141:3914–3915

    Article  Google Scholar 

  • You Q, Luo J, Jin H, et al. Cross-modality Consistent Regression for Joint Visual-Textual Sentiment Analysis of Social Multimedia[J]. 2016:13–22.

  • Zhang Y. Research on English Listening and Speaking Teaching Model Based on Computer New Media Technology[C]//Journal of Physics: Conference Series. IOP Publishing, 2020, 1648(3): 032174.

  • Zhao X, Wang Y, Liu Y et al (2019) Multimedia based teaching platform for English listening in universities[J]. Int J Emerg Technol Learn 14(4):160–168

    Article  Google Scholar 

  • Zhou X, Ye Z, Liu X et al (2017) Chi-Square Distribution-Based Confidence Measure Channel Estimation Method in OFDM Systems[J]. IETE J Res 63(5):1–9

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by 2019 Program for Young Innovative Talents of Humanities and Social Science in Higher Education of Guangdong (No.2019GWQNCX033).

Funding

This work was supported by 2019 Program for Young Innovative Talents of Humanities and Social Science in Higher Education of Guangdong (No.2019GWQNCX033).

Author information

Authors and Affiliations

  1. School of International Cooperation, Guangdong Polytechnic of Science and Technology, Zhuhai, 519090, China

    Yingting Zhang

  2. Shenzhen Plant Resource Technology Co., Ltd, Shenzhen, 518000, China

    Zewei Huang

Authors
  1. Yingting Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zewei Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Corresponding author

Correspondence to Yingting Zhang.

Ethics declarations

Conflict of interest

All Authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Huang, Z. Application of multimedia network english listening model based on confidence learning algorithm for speech recognition. Int J Syst Assur Eng Manag 13 (Suppl 3), 1091–1101 (2022). https://doi.org/10.1007/s13198-021-01433-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-021-01433-z

Keywords

Search

Navigation