In this study the author describes an algorithm that can discriminate transcoded from true lossless audio files, i.e. a file that was obtained by directly ripping a genuine audio CD from a file that was decoded from a lossy audio format (e.g. MP3, AAC) and re-encoded with a lossless format. This algorithm should allow both consumers and online music dealers to check the authenticity of lossless music files. Although research focuses on the MPEG AAC codec, the approach can also be applied to the MP3 codec. It is based on the detection of quantization errors in the time-frequency domain without using machine learning. Tests with a large database of 1576 audio files, original and transcoded with AAC from iTunes, show null false positive ratios and very low false negative ratios, possibly null for high-precision settings, which is better than other methods. It was shown that a perfectly accurate classification can be reached, provided a sufficiently long computation time is allowed. Furthermore, the method is naturally immune to truncation of audio files and global gain modification.
https://www.aes.org/e-lib/browse.cfm?elib=19892
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is free for AES members and E-Library subscribers.
Learn more about the AES E-Library
Start a discussion about this paper!
