Construction of complex environment speech signal communication system based on 5G and AI driven feature extraction techniques

In daily life, the most direct and important way of human communication is voice. With the rise of the Internet and the development of communication technology, the proportion of non voice signals such as image and data in communication system is increasing. However, in most communication systems, voice transmission function is generally required, so it is still one of the necessary functions for many communication systems to transmit voice information effectively. With the rapid development of the Internet, especially the recent 5G technology commercial and future civil, human–computer interaction will become more and more intelligent in the future, which also poses a greater challenge to speech recognition as a human–computer interface. Noise interference is one of the biggest obstacles to the practical application of speech system. Although a large number of noisy data based on deep learning can solve part of the noise robustness problem, non-stationary noise interference is still a great challenge for speech recognition system in very low SNR complex scenes. In addition, in the multi information fusion communication system, there are many kinds of data to be transmitted, and there are high requirements for bandwidth and storage space. Hence, this paper studies the construction of voice signal communication system based on the artificial intelligence and 5G technology. The model is designed and implemented considering the complex scenarios. The performance is validated through the simulations compared with the state-of-the-art methods.