Speech Recognition Method for English Translators in Noisy Environments Based on Attention Mechanism
Liu Long · International Journal of High Speed Electronics and Systems · 2025
In this paper, a novel speech recognition method is proposed to improve the recognition efficiency and accuracy of English translators in noisy environments. First, by using an efficient noise suppression algorithm, the interference of background noise to the recognition process is significantly reduced. Then, deep neural networks are used to enhance the adaptability to various noise environments, further improving the stability and accuracy of recognition. In the feature extraction stage, this paper focuses on Mel-Frequency Cepstral Coefficients and Mayer filter bank features, which lays a solid foundation for the application of non-autoregressive Transformer. Finally, non-autoregressive Transformer technology is adopted in this study, which gives full play to its advantages in processing speed and efficiency, ensuring fast and accurate speech recognition in complex noise environments. On the whole, the method in this paper not only improves the performance of speech recognition in noisy environment, but also provides a valuable reference for the research and application in related fields.