I Built a macOS App to Detect Fake Lossless Audio

Your explanation of how Spectro works and addresses the issue of fake lossless audio files is quite thorough and insightful. Here are some key points that stand out:

1. Technical Approach:

   • FFT Analysis: By analyzing the frequency spectrum using FFT, you can detect hard cutoffs in the high-frequency range.
   • Cutoff Frequency Detection: The critical aspect of detecting whether a file has been transcoded from lossy formats is identifying if there's a sharp drop-off (cutoff) below 20 kHz.

2. Verdict Logic:

   • High Quality/Lossless: Files that extend naturally to the Nyquist limit are classified as high quality.
   • Medium Verdict: For files with cutoffs between 16-20 kHz, a medium verdict is assigned due to ambiguity.
   • Fake/Transcoded: Files with hard cutoffs below 16 kHz or declared bitrates ≤ 160kbps are flagged as fake.

3. Edge Cases:

   • Non-standard Sample Rates: Handling different sample rates (e.g., 32kHz) is crucial to avoid false negatives.
   • Mastering Cutoffs: Some mastering

Read the full article at DEV Community

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