基于特征的压缩音频编码器类型辨识

Feature-based Classication of Compressed Audio Stream Encoder

当前的数字音频编码算法使用复杂的模型来最大化编码效率,同时使得失真最小。由于这种复杂性,对相同未压缩的输入音频,采用不同编码器压缩音频时往往会产生不同的输出音频。在统计分析了已压缩音频码流特征的基础上,采用SVM(支持向量机)分类器来确定最可能的13种编码器的矢量特性,提出了一种方法来辨识基于MPEG-1 Layer III(MP3)标准音频文件的编码器类型。测试结果表明准确度可以达到95%左右,并且可以通过加入新的码流特征来进一步提高辨识结果的准确性。因此,这种方法可以被视为一种辨识MP3编码器类型的通用方法。

Today＇s digital audio coding algorithms use sophisticated models to maximize the encoding rate while minimize theaudible distortlon.As a result of this complexity, different implementations of one encoding standard tend to produce varying outputstreams for the same uncompressed input data. The paper presents a method to distinguish between the encoding schemes used tocompress MPEG1 Layer-3 （MP3） audio files on the basis of the statistical features that can be extracted from the compressed streams.The method adopts a SVM machine learning classifier to determine the most likely encoder from a vector of 13 features.The experimentalresults show that the accuracy can be up to 95% ,and the accuracy of the identification results can be further improved by adding newcharacteristics from the code flow.So the method can be considered as a generic tool to increase the overall reliability of steganalysis ofMP3 files.