Research on Speech Accurate Recognition Technology Based on Deep Learning DNN-HMM

In recent years, with the rapid development of artificial intelligence technology, human auditory intelligence perception has received extensive attention. The human-like auditory intelligent speech separation of robots in complex acoustic environment is studied. Through in-depth learning of key technologies such as DNN-HMM, a new deep network cluster structure, optimization objectives and deep learning algorithm capable of denoising in complex frequency domain are proposed to improve the accuracy of speech recognition, solve the problem of speech separation in human-like hearing in harsh environments, realize high-quality auditory perception in real environments, and enhance intelligence in far-field and complex acoustic environments. Human-computer interaction performance.