录音设备的建模和识别算法

本文提出了一种录音设备的建模和识别算法。在特征选择方面，考虑到音频段中的静音包含了与正常语音一样的设备信息，并且不受说话人、文本、情感等因素的影响，因此从静音段中提取出表征录音设备“机器指纹”的特征，并用谱减法去除其中的背景噪声。在识别模型方面，利用设备通用背景模型构建反对设备模型；在设备通用背景模型的基础上，利用少量的特定设备数据，通过MAP自适应算法获得相应录音设备的模型。最后通过归一化似然度得分对输入的特定录音设备的语音样本进行分类判决。实验结果表明，对于9种不同录音设备的平均正确识别率为87.42%，并考察了不同因素对本文算法的影响，验证了本文算法的有效性和可靠性。 

A Modelling and Identification Algorithm of Recording Devices

This paper proposes a modeling and identification algorithm of recording devices. The features of “the fingerprints of recording devices” are extracted from the silence periods of a speech for the purpose of recording devices identification, because the same device information can be obtained from both silence and speech periods in an audio sequence but the device information is not effected by speaker information, texture information and emotion information in the silence periods. On the one hand, the recording device universal background model is used to establish the model of inverse devices. On the other hand, the model of specific recording device is achieved by adapting the recording device universal background model through MAP adaptation algorithm. Finally, the normalized log-likelihood is used to classify the specific categories of the recording devices of the input speech samples. The results of experiments indicate that the average accuracy of recording device identification on 9 recording devices is 87.42% and the effects of different factors on the impact of the proposed algorithm are investigated, which proves the effectiveness and reliability of the proposed algorithm.