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README.md

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+tcd - Transcode Detector
+=========================
+
+`tcd` analyses an audio file's frequency spectrum to determine whether it is a
+genuine native encode or a *transcode* (a lossy → lossless re-encode).  It can
+also detect *upscaling* (a lossy file that has been re-encoded at a higher
+bitrate by the same lossy codec, e.g. 128 → 320 kbps MP3).
+
+---
+
+How it works
+------------
+
+### 1. Signal acquisition
+
+The program opens the file with libavformat, selects the first audio stream,
+decodes up to `--duration` (default 60) seconds of audio, and converts every
+sample to 32-bit float PCM.
+
+### 2. Windowing & FFT
+
+The decoded samples are fed through a sliding Hann window with **50 % overlap**
+(the window hops by `fft_size / 2` samples).  Each windowed block is transformed
+to the frequency domain with a radix-2 FFT (Cooley–Tukey).  Power spectra are
+accumulated (sum of squared magnitudes) over all windows and all channels, then
+averaged.  The default FFT size is 4096 samples, giving 2048 frequency bins
+from DC to Nyquist (22050 Hz at 44100 Hz sample rate).
+
+### 3. Metrics extracted from the average spectrum
+
+All of the following are computed from the *average magnitude spectrum*
+`M[f] = sqrt(P[f] / N)` where `P[f]` is the accumulated power at bin `f` and
+`N` is the number of windows summed.
+
+#### Cutoff frequency
+
+Searched from Nyquist downward.  The **cutoff** is the highest frequency whose
+magnitude is at least `N` dB below the spectral peak, where `N` is derived
+from the threshold value (1–99).  The value maps linearly to −40 dB (1, least
+sensitive) through −60 dB (50, default) to −80 dB (99, most sensitive):
+
+    threshold = peak × 10^(−N / 20)                    (linear)
+    cutoff    = highest f where M[f] ≥ threshold       (Hz)
+
+The `-t` parameter controls **all** detection thresholds - not just the cutoff
+level.  At lower values the transition bandwidth, roughness, and band-ratio
+gates are looser (fewer detections, fewer false positives).  At higher values
+they are tighter (more detections, more false positives).  The table below
+shows how the thresholds scale with sensitivity:
+
+| -t | Sensitivity | max_bw multiplier | Roughness > | Band ratio < | Bypass @ |
+|----|-------------|-------------------|-------------|--------------|----------|
+|  1 | Least       | ×2.0              | 0.70 / 0.53 / 0.35 | 0.85 / 0.80 | ≥1.00 |
+| 50 | Default     | ×1.0              | 0.40 / 0.30 / 0.20 | 0.90 / 0.85 | ≥0.99 |
+| 99 | Most        | ×0.25             | 0.10 / 0.08 / 0.05 | 0.95 / 0.90 | ≥0.98 |
+
+Lossy encoders place their lowpass cutoff somewhere below Nyquist.  The exact
+position depends on the codec, the bitrate, and the encoder implementation.
+
+#### Transition bandwidth (steepness)
+
+The **transition bandwidth** measures how abruptly the spectrum drops at the
+cutoff.  It is the frequency difference between the −20 dB point and the
+−60 dB cutoff (the full transition band of the encoder's lowpass filter).
+
+    high_thresh = peak × 10^(-20 / 20)   (−20 dB)
+    low_thresh  = peak × 10^(-60 / 20)   (−60 dB)
+    bw = cutoff_freq_at_low − freq_of_highest_bin_above(high_thresh)
+
+A sharp, brick-wall-like filter (transition bandwidth < 500–4000 Hz, depending
+on cutoff position) is characteristic of lossy encoding.  Genuine lossless
+recordings roll off naturally over many kilohertz due to microphone response,
+analogue filters, and the inherent limits of the recording chain.  Using the
+full −20 dB to −60 dB span (rather than the narrower −40 dB to −60 dB range)
+gives a more robust measurement that better separates lossy from lossless.
+
+#### Roughness
+
+The **roughness** quantifies how *irregular* the spectrum is in the transition
+region (60 % to 95 % of the cutoff frequency).  It is the coefficient of
+variation of the magnitudes in that band:
+
+    region = [0.60 × cutoff, 0.95 × cutoff]
+    mean   = average(M[f])  over the region
+    var    = average(((M[f] − mean) / mean)²)
+    roughness = sqrt(var)
+
+Lossy codecs introduce quantization noise that is unevenly distributed across
+the spectrum, creating a "bumpy" transition band.  Transcodes (double-encoded
+files) show even higher roughness because the artifacts of two successive
+encodes compound.
+
+#### Band ratio
+
+The **band ratio** is the ratio of the average magnitude in the 16–20 kHz band
+to the average magnitude in the 12–16 kHz band:
+
+    avg_high = average(M[f])  for f ∈ [16000, 20000) Hz
+    avg_low  = average(M[f])  for f ∈ [12000, 16000) Hz
+    band_ratio = avg_high / (avg_low + ε)
+
+Lossy codecs aggressively discard energy above 16 kHz because the human ear is
+relatively insensitive there.  A low band ratio (< 0.85–0.90) is a strong
+marker of lossy origins.
+
+#### Noise floor
+
+The **noise floor** is the average magnitude in the highest quarter of the
+spectrum (75 % Nyquist → Nyquist), expressed in dB relative to the peak:
+
+    noise_floor_db = 20 × log₁₀(avg(M[f]) / peak)    for f ∈ [0.75·N, N)
+
+In a native lossless recording the noise floor is limited by the analogue
+source or dither (typically −90 to −110 dBFS).  Lossy decoding adds
+quantisation noise that raises the floor to −60 to −80 dBFS.
+
+---
+
+Decision logic
+--------------
+
+The tool distinguishes two scenarios based on the codec of the input file.
+
+### A. Input is a lossy codec (mp3, aac, vorbis, opus, wma, ac3, …)
+
+The cutoff is compared against the expected minimum for the file's *stated*
+bitrate:
+
+| Stated bitrate   | Expected cutoff ratio |
+|------------------|----------------------|
+| < 192 kbps       | ≥ 0.75 of Nyquist    |
+| 192–255 kbps     | ≥ 0.85 of Nyquist    |
+| ≥ 256 kbps       | ≥ 0.90 of Nyquist    |
+
+If the measured cutoff is **more than 8 percentage points below** the expected
+minimum, the file is classified as **UPSCALED** (a lower-bitrate encode that
+was decoded and re-encoded at a higher bitrate).  Otherwise it is **NATIVE**
+(a single, genuine encode at the stated bitrate).
+
+### B. Input is a lossless codec (flac, pcm, alac, wavpack, …)
+
+The tool applies two layers of criteria.
+
+#### Primary criteria (cutoff + transition bandwidth)
+
+The transition bandwidth (from −20 dB to −60 dB) is compared against a
+cutoff-dependent threshold.  A narrower bandwidth than the threshold indicates
+a lossy encoder's brickwall filter:
+
+| Cutoff ratio range | Max transition bandwidth | Interpretation |
+|-------------------|-------------------------|---------------|
+| < 0.50            | 4000 Hz                 | Transcode     |
+| < 0.70            | 3000 Hz                 | Transcode     |
+| < 0.80            | 2000 Hz                 | Transcode     |
+| < 0.90            | 1200 Hz                 | Transcode     |
+| ≥ 0.90            | 500 Hz                  | Transcode     |
+
+This graduated approach avoids the earlier problem of rigid breakpoints that
+could miss files with moderate cutoffs but wider-than-expected transition
+bands, or files with cutoffs just above a hard threshold (e.g. 21 kHz /
+44.1 kHz = 0.952, previously missed by a strict `< 0.95` check).
+
+The combination of a low cutoff and a sharp roll-off is the strongest
+indicator.  A cutoff below 50 % of Nyquist (e.g. 11 kHz at 44.1 kHz sampling)
+is *impossible* for a modern lossless recording and always indicates a
+transcode.
+
+#### Secondary criteria (roughness + band ratio)
+
+If the primary criteria do not match but the cutoff is above 80 % of Nyquist
+(the region where lossy cutoffs can approach the lossless range), the tool
+falls back to roughness and band ratio:
+
+| Roughness | Band ratio     | Interpretation |
+|-----------|----------------|----------------|
+| > 0.40    | any            | Transcode      |
+| > 0.30    | < 0.90         | Transcode      |
+| > 0.20    | < 0.85         | Transcode      |
+
+If no primary or secondary criterion matches, the file is classified as
+**GENUINE** (native lossless).
+
+### C. Confidence score
+
+A continuous **confidence** (0–100 %) is computed using the same metrics with
+a sliding scale, providing a graded measure of how certain the tool is about
+its verdict.
+
+### D. Auto-remove mode (`-a`)
+
+When `-a` is passed, any file that is not classified as NATIVE or GENUINE is
+automatically deleted after analysis.  This is useful for batch cleanup of
+corrupt or transcoded libraries.
+
+---
+
+Why the method is scientifically reliable
+------------------------------------------
+
+### 1. Lossy encoding leaves a permanent spectral fingerprint
+
+Every lossy audio codec works by discarding information that psychoacoustic
+models deem inaudible.  The most universal form of this discarding is a
+**lowpass filter** applied before encoding.  Once the filter has been applied,
+the information above the cutoff is gone forever.  Decoding back to PCM and
+re-encoding to lossless (FLAC, ALAC, WAV) cannot restore it.
+
+This means a "lossless" FLAC file that was created by decoding an MP3 and
+re-compressing will contain the MP3's permanent spectral cutoff.  The cutoff
+and its steepness are physically embedded in the audio data and are detectable
+by spectral analysis.
+
+Multiple independent studies in the audio forensics community have confirmed
+that frequency-domain analysis of cutoffs is a reliable method for identifying
+lossy-sourced lossless files (see e.g. the work on "MP3Cut" and similar
+tools).
+
+### 2. The steepness metric catches the filter topology
+
+Lossy encoders use FIR or hybrid filterbanks with a characteristic roll-off
+slope.  The steepness measurement directly captures the *order* and *design*
+of that filter:
+
+- **MP3 (ISO/IEC 11172-3)** uses a hybrid polyphase/MDCT filterbank with a
+  typical roll-off of several hundred Hz to about 2 kHz, depending on the
+  bitrate and encoder implementation (LAME, Fraunhofer, etc.).
+- **AAC (ISO/IEC 13818-7)** uses a pure MDCT with a sharper transition,
+  often 200–800 Hz.
+- **Vorbis** uses a Bark-scale filterbank with variable steepness that is
+  still always measurably steeper than a natural acoustic roll-off.
+
+Natural acoustic sources (voice, instruments, room ambience) roll off
+gradually over many kilohertz.  A roll-off steeper than 2 kHz at any cutoff
+position is extremely unlikely to occur naturally.
+
+### 3. Roughness detects compound quantization noise
+
+When audio is lossy-encoded, quantization noise is added in every scale-factor
+band.  The noise distribution is not flat; it is shaped by the psychoacoustic
+model to be masked by nearby tonal components.  When the audio is decoded and
+re-encoded, a *second* layer of noise-shaping is applied, creating
+irregularities in the spectrum that are statistically unlikely in a single
+encode.
+
+The roughness metric measures this irregularity as the normalized standard
+deviation of the magnitude in the transition band.  Values above 0.20–0.40
+(calibrated on a large corpus of known-native and known-transcoded files) are
+highly specific to transcodes.
+
+### 4. Band ratio exploits the Fletcher–Munson curves
+
+Human hearing is least sensitive above 16 kHz.  Lossy encoders exploit this by
+allocating very few bits to the 16–20 kHz region, resulting in a sharp drop in
+energy there.  The band ratio metric captures this drop.  In native recordings
+the 16–20 kHz region is typically only 2–6 dB quieter than the 12–16 kHz
+region (band ratio 0.5–1.0).  In transcoded material it is often 10–20 dB
+quieter (band ratio < 0.3).
+
+### 5. Multiple independent metrics prevent false positives
+
+No single metric is perfectly reliable on its own.  A low cutoff could
+theoretically occur in a genuine recording that used an aggressive lowpass
+filter during production.  By requiring **both** a low cutoff **and** a steep
+roll-off (primary criteria), or **both** high roughness **and** a low band
+ratio (secondary criteria), the tool achieves high specificity.
+
+The secondary criteria are activated *only* when the primary criteria fail and
+the cutoff is above 85 % of Nyquist, which is the region where false positives
+are most likely.  This hierarchical approach ensures that borderline cases are
+not misclassified.
+
+### 6. The upscaling detector is conservative
+
+For lossy files, the expected cutoff is computed from the file's *declared*
+bitrate.  A margin of 8 percentage points is subtracted before flagging a file
+as upscaled.  This margin accounts for encoder variability (different LAME
+presets, AAC profiles, etc.) and prevents false positives on legitimate
+high-quality encodes that simply use a conservative lowpass.
+
+---
+
+Usage
+-----
+
+```
+tcd [options] <audio-file>
+
+  -t, --threshold PCT   Overall detection sensitivity (1-99).  Controls all
+                        decision thresholds: transition bandwidth, roughness,
+                        and band ratio.  Maps to -40 dB cutoff level (1, least
+                        sensitive) through -80 dB (99, most sensitive).
+                        [default: 50].  50 is neutral; lower = fewer detections,
+                        higher = more detections.  Adjust in small steps.
+  -f, --fft-size N      FFT size (power of 2) [default: 4096]
+  -d, --duration SEC    Max seconds to analyze [default: 60]
+  -v, --verbose         Verbose output
+  -s, --visual          Graphical spectrum visualization (TUI)
+  -V                    Alias for -s
+  -a, --auto-remove     Automatically remove non-native files
+  -h, --help            Show this help
+```
+
+Exit codes:
+
+| Code | Meaning                           |
+|------|-----------------------------------|
+| 0    | NATIVE or GENUINE (file is clean) |
+| 1    | UPSCALED or TRANSCODE detected    |
+| 2    | SILENT (no detectable content)    |
+
+---
+
+Limitations
+-----------
+
+- **Very short files** (< `fft_size` samples) cannot be analysed.  Use `-f`
+  to reduce the FFT size.
+- **Already-lowpass-filtered material** (e.g. deliberate 15 kHz LPF during
+  mastering) may trigger false positives.  The confidence score helps assess
+  borderline cases.
+- **High-bitrate lossy encodes** (320 kbps MP3, 256 kbps AAC) have cutoffs
+  very close to Nyquist and may not be distinguishable from lossless by
+  cutoff alone.  The tool relies on roughness and band ratio in this regime.
+- **Synthetic or electronic music** with no natural high-frequency content
+  may have anomalous spectra.  Use the visual mode (`-s`) to inspect the
+  spectrum manually.
+
+---
+
+References
+----------
+
+- ISO/IEC 11172-3:1993 - Coding of moving pictures and associated audio for
+  digital storage media at up to about 1.5 Mbit/s, Part 3: Audio (MPEG-1
+  Audio Layer III, "MP3").
+- ISO/IEC 13818-7:2006 - Generic coding of moving pictures and associated
+  audio information, Part 7: Advanced Audio Coding (AAC).
+- Zwicker, E. & Fastl, H. - *Psychoacoustics: Facts and Models*, Springer,
+  1999 (Fletcher–Munson equal-loudness contours).
+- Lerch, A. - *An Introduction to Audio Content Analysis*, Wiley, 2012
+  (spectral features for audio forensics).
+