Evaluation of Interference Effect of Speech Communication System
Ming Hao, Sen Wang · 2021 13th International Symposium on Antennas, Propagation and EM Theory (ISAPE) · 2021
With the ubiquitous wireless network access, the limited frequency band resources and the rapid increase of equipment make the interference frequency higher and higher. Whether in military or civil fields, speech signal is one of the main signals transmitted by modern communication system. The speech quality output by communication system is the key factor to evaluate the overall performance. Evaluating the performance of those systems is of great importance to promote the quality of speech communication. In this paper, the deep convolution neural network is used to evaluate the quality of speech communication. Compared with the traditional machine learning evaluation method, the non-reference evaluation model is realized, and the evaluation accuracy has been improved by 8%.