English listening and speaking ability evaluation model fusing computer vision and speech recognition algorithms
Abstract
Traditional English listening and speaking ability evaluation mostly uses speech recognition algorithm as the evaluation method, but evaluation features are rather limited, which leads to insufficient accuracy of the results. In order to improve the evaluation effect of English listening and speaking ability evaluation model, this paper constructs a feature tagging corpus and built a real-time speech interaction system based on the fusion of speech and visual signals, combines it with the speech recognition algorithm to build an English listening and speaking ability evaluation model. Finally, this paper verifies the effectiveness of the English listening and speaking ability evaluation model through simulation experiments, which provide a specific research direction for the subsequent English listening and speaking ability evaluation, and also provides a reference for the construction of an intelligent platform for the subsequent oral English evaluation.
Identifier Metadata
| Identifier | 110.0806/CON.2026.00777 |
| Canonical | mdoi:110.0806/CON.2026.00777 |
| Resolver URL | https://mdoi.org/110.0806/CON.2026.00777 |
| Resource URL | Open resource |
| Document URL | Open document |
| Content Type | Article |
| Authors | Yihui Zeng |
| Year | 2025 |
| Depositor | Convergence Chronicles Organisation |
| Prefix | 110.0806 |
| Registered | July 27, 2026 |
| Updated | July 27, 2026 |
| Status | Active |
| Visibility | Public |
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