Application of Intelligent Speech Recognition Technology Based on Wavelet Algorithm in Chinese Oral Teaching

As one of the core technologies in the field of artificial intelligence (AI), intelligent automatic speech recognition (ASR) technology is gradually changing people's communication methods, providing great convenience for cross language communication. In the field of education, especially in Chinese oral teaching, the application of ASR technology will undoubtedly bring revolutionary changes to teaching methods and learning outcomes. However, speech signals are often affected by various noises during transmission, leading to a decrease in the quality of speech signals and affecting the accuracy and effectiveness of ASR. Based on this, this article proposes an intelligent ASR technology based on wavelet algorithm and deep learning (DL), aiming to solve this problem. Wavelet algorithm, as a time-frequency analysis tool, can effectively extract feature information from speech signals, suppress noise interference, and improve the robustness of ASR. DL technology, on the other hand, constructs complex neural network models to achieve deep learning and understanding of speech signals, further improving the accuracy of ASR. The experimental results show that the method proposed in this article can effectively improve the accuracy of ASR, help students correct pronunciation errors, and improve their Chinese oral proficiency.