关键词: 变异系数, 高斯混合模型, 回放语音检测, 梅尔倒谱系数, 滤波器组

Abstract: With the development of speech technology, various kinds of phishing speech represented by playback speech have brought serious challenge for voiceprint authentication system and audio forensics technology. Aiming at the attack problem of playback speech to voiceprint authentication system, a new detection algorithm based on modified cepstrum feature was proposed. Firstly, the coefficient of variation was used to analyze the difference between the original speech and the playback speech in the frequency domain. Secondly, a new filter bank composed of inverse-Mel filters and linear filters was used to replace Mel filter bank in the process of extracting Mel Frequency Cepstral Coefficients (MFCC) pertinently, and then the modified cepstrum feature based on the new filter bank was obtained. Finally, Gaussian Mixture Model (GMM) was utilized as the classifier to classify and discriminate speech. The experimental results show that, the modified cepstrum feature can effectively detect the playback speech, and its equal error rate is about 3.45%.

Key words: coefficient of variation, Gaussian Mixture Model (GMM), playback speech detection, Mel Frequency Cepstral Coefficients (MFCC), filter bank