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Audio codec identification from coded and transcoded audios

机译:从编码和转码音频中识别音频编解码器

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摘要

A novel technique is presented to identify the codec of a coded audio. The technique does not perform decoding, utilize any coding metadata, or assume information about the structure describing the bit stream format of a codec. The underlying idea of the technique is that the design choices governing the compression level, audio quality and complexity of a codec will reveal themselves on the coded audio. To exploit this, the technique samples 2-4 kilobytes of data from a coded audio and analyzes the randomness and chaotic nature of the sampled data to build statistical models that represent encoding process associated with different codecs. In experiments, we utilize 16 of the most popular audio codecs used for high quality audio compression and in PSTNs, cellular networks, and VoIP networks by setting encoding parameters of each codec to its most commonly used values. Results show that the codec of an encoded audio can be identified with an accuracy of more than 95 percent. Other experiments considering several transcoding scenarios were also performed. Those results show that the scheme can even discriminate the first encoder of a doubly-encoded audio with an accuracy range of around 80 to 90 percent or more as long as the second codec operates on higher bit rates than the first one.
机译:提出了一种新颖的技术来识别编码音频的编解码器。该技术不执行解码,不使用任何编码元数据或假设有关描述编解码器的比特流格式的结构的信息。该技术的基本思想是,控制压缩级别,音频质量和编解码器复杂性的设计选择将在编码音频上展现自己。为了利用这一点,该技术从已编码的音频中采样了2-4 KB的数据,并分析了采样数据的随机性和混沌性质,以建立表示与不同编解码器关联的编码过程的统计模型。在实验中,通过将每个编解码器的编码参数设置为其最常用的值,我们利用了16种最流行的音频编解码器用于高质量音频压缩,并用于PSTN,蜂窝网络和VoIP网络。结果表明,可以以95%以上的精度识别编码音频的编解码器。还进行了考虑几种转码方案的其他实验。这些结果表明,只要第二编解码器以比第一个编解码器更高的比特率工作,该方案甚至可以以大约80%到90%或更高的精度范围区分双编码音频的第一个编码器。

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