Research on Speech Command Recognition Algorithm for Power Systems Based on Machine Learning
Enhancing the accuracy,real-time capability,and robustness of speech command recognition technol-ogy in power systems is crucial for improving system reliability and stability.This research first analyzes prepro-cessing methods for speech signals in power systems,including techniques such as signal enhancement,speech frame segmentation,and spectrum smoothing.An algorithm based on Gaussian Mixture Models(GMM)for speech command recognition is designed.Experimental results demonstrate that the algorithm achieves higher rec-ognition accuracy and real-time performance in power system speech control scenarios,while maintaining robust-ness suitable for complex power system environments.The study also identifies areas for further improvement and enhancement to enhance algorithm performance for broader practical applications.
power systemsmachine learningspeech commandspeech recognitionsignal processing
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