Design of Intelligent Speech Recognition System Based on Data Analysis Algorithm

With the rapid development of artificial intelligence and big data technology, the application of intelligent speech recognition system in various fields is gradually expanding. However, traditional intelligent speech recognition systems still have some limitations in terms of user satisfaction, accuracy and speed. In order to overcome the limitations of the traditional intelligent speech recognition system and further improve its performance, this paper introduces an intelligent speech recognition system based on data analysis algorithms. The system utilizes large-scale datasets for training and analysis to improve the recognition accuracy of speech signals and the overall performance of the system. The purpose of this research is to explore the advantages and disadvantages of an intelligent speech recognition system based on data analysis algorithms, and to further improve the performance of the system in noisy environments. This paper adopts the research method of experimental verification, conducts a comprehensive analysis and evaluation of the intelligent speech recognition system based on data analysis algorithm, and puts forward suggestions for improving the algorithm. Research shows that the intelligent speech recognition system based on data analysis algorithm has obvious advantages in terms of user satisfaction, accuracy and speed. However, the system still faces challenges such as noisy environment and false recognition rate. In order to improve the system performance, we need to improve the noise processing algorithm, optimize the algorithm, and increase the training data. Through the research of this paper, we provide useful reference and guidance for the development and application of intelligent speech recognition system.