通信语音干扰效果评估方法

通信语音干扰效果评估，是指对语音通信系统接收的受扰语音信号进行分析，确定语音信号被干扰程度的技术。准确地评估干扰效果是研制通信对抗设备、评估电子对抗态势以及了解通信质量等活动的重要依据。针对超短波通信干扰系统，提出了基于梅尔频率倒谱系数(MFCC)特征、小波统计特征和感知特征的统计测度，结合最小二乘、反向传播(BP)神经网络以及支持向量回归(SVR)拟合回归模型的评估系统，其预测值和主观评估值的相关系数达到0.9以上，保障了该干扰评估系统的实用性。研究了基于深度学习的无参考评估方法，并利用实测数据验证了其有效性，准确率达到了87%，高于多测度融合评估方法。

Evaluation method of communication speech interference effect

The evaluation of speech interference effect refers to the technology of analyzing the disturbed speech received by the communication system to determine speech interference effect level. Accurately evaluating the interference effect is of great significance to the development of communication countermeasure equipment, the assessment of the situation of electronic countermeasures and understanding of communication quality. As for ultra-short wave communication jamming system, a method is proposed based on Mel-Frequency Cepstral Coefficients(MFCC) features, wavelet statistical features and perceptual features, combined with the least squares, the Back Propagation(BP) neural network and Support Vector Regression(SVR) fitting regression model, the correlation coefficient between the predicted value and subjective evaluation value is above 0.9, which guarantees the practicability of the evaluation system. Secondly, the non-reference evaluation method is studied based on deep learning, and the measured data is adopted to verify the effectiveness of this method. The accuracy rate is 87%, higher than that of the multi-measure fusion evaluation method.