Research on Modeling of Speech Recognition Based on Deep Learning
DOI:
https://doi.org/10.53469/jtpms.2025.05(4).11Keywords:
Deep learning, Speech recognition, Feature extraction, DFSMN modelAbstract
With the development of technology, the application of speech recognition is becoming increasingly widespread, and intelligent speech recognition has great significance. The article introduces the working mechanism and classification of speech recognition systems, and designs the system development environment and framework. Design the collection of speech datasets, preprocessing of speech data, feature extraction of speech data, construction of acoustic models, and construction of language models for deep learning based Chinese speech recognition. This study is capable of self recording speech or uploading speech to a server for Chinese recognition, and supports the function of translating recognized Chinese into English. This study can lay the foundation for further in-depth research on speech recognition.
References
Wang, Y., Yang, T., Liang, H., & Deng, M. (2022). Cell atlas of the immune microenvironment in gastrointestinal cancers: Dendritic cells and beyond. Frontiers in Immunology, 13, 1007823.
Li, X., Wang, J., & Zhang, L. (2025). Gamifying Data Visualization in Smart Cities: Fostering Citizen Engagement in Urban Monitoring. Authorea Preprints.
Wang, J. (2025). Bayesian Optimization for Adaptive Network Reconfiguration in Urban Delivery Systems.
Li, T. (2025). Enhancing Adverse Event Monitoring and Management in Phase IV Chronic Disease Drug Trials: Applications of Machine Learning.
Li, X., Wang, J., & Zhang, L. (2025). Named entity recognition for smart city data streams: Enhancing visualization and interaction. Authorea Preprints.
Yang, J. (2025). Application of LightGBM in the Chinese Stock Market.
Song, X. (2025). User-Centric Internal Tools in E-commerce: Enhancing Operational Efficiency Through AI Integration.
Wu, W. (2024). Research on cloud infrastructure for large-scale parallel computing in genetic disease.
Chen, J. (2025). Leveraging Scalable Cloud Infrastructure for Autonomous Driving Data Lakes and Real-Time Decision Making.
Lin, Y., Liu, J., Cao, Y., Cao, Y., & Wang, Z. (2025). Transfer learning-enhanced modelling of annular aperture arrays and nanohole arrays. Physica Scripta, 100(3), 036003.
Gong, C., Lin, Y., Cao, J., & Wang, J. (2024, October). Research on Enterprise Risk Decision Support System Optimization based on Ensemble Machine Learning. In Proceeding of the 2024 5th International Conference on Computer Science and Management Technology (pp. 1003-1007).
Bohang, L., Li, N., Yang, J. et al. Image steganalysis using active learning and hyperparameter optimization. Sci Rep 15, 7340 (2025). https://doi.org/10.1038/s41598-025-92082-w
