tcdweb — Transcode Detector (Web Version)

tcdweb is a browser-based audio authenticity analyzer that determines whether an audio file is a genuine native encode or a transcode (lossy → lossless re-encode). It can also detect upscaling (a lossy file re-encoded at a higher bitrate by the same lossy codec, e.g. 128 → 320 kbps MP3).

This is the web version of tcd, the original CLI tool. At this point tcdweb is a complete, independent fork with its own codebase, its own analysis engine, and its own UI. It runs entirely in the browser via the Web Audio API — no server-side processing, no file uploads, no FFmpeg dependency, and no command line needed.

Obligatory AI-slop disclaimer

tcdweb is 98% vibe-coded (a.k.a. "ai slop"). If that's a problem for you, please kindly just use a different tool. There is also absolutely NO guarantee this will work reliably, be useful in any way, or even make any sense whatsoever.

What it does

Drag or load an audio file, and tcdweb will:

1. Decode it client-side using the browser's built-in decoder
2. Compute the frequency spectrum via a Hann-windowed FFT (4096-point, 50% overlap)
3. Extract five key metrics (see below)
4. Apply a two-layer verdict system to classify the file
5. Display a detailed decision log, confidence score, and interactive charts

It includes a realtime FFT analyzer, a waveform viewer with playback, BPM detection, metadata tag parsing (ID3v1/v2, FLAC, APE), and a full data table with every computed value.

Key metrics

• Cutoff: highest frequency with measurable energy (as Hz and % of Nyquist). Lossy codecs chop off high frequencies — the lower the cutoff, the more aggressive the compression.
• Steepness (Transition Bandwidth): how abruptly the spectrum drops at the cutoff point. Lossy encoders produce sharp brick-wall filters (low steepness).
• Noise Floor: average noise level in the top quartile of the spectrum. Lossy quantization raises the noise floor.
• Roughness (Coefficient of Variation): how jagged/bumpy the spectrum is before the cutoff. Lossy encoding introduces quantization noise that creates spectral scalloping.
• Band Ratio: energy ratio between 16–20 kHz and 12–16 kHz. Transcodes show an unnatural dip in the top octave.

Supported formats

Support depends on the browser's built-in decoder (all modern browsers support the most common formats).

Verdicts

Detection logic

The verdict is determined in two layers:

Layer 1 (Primary) — Cutoff + Steepness. A low cutoff combined with a sharp drop (low steepness) is a definitive sign of a lossy encoder's lowpass filter.

Layer 2 (Secondary) — Roughness + Band Ratio. Applied when the cutoff is high enough to pass Layer 1. Catches transcodes where the cutoff is near Nyquist but the spectrum still shows quantization artifacts.

Lossy files are checked for upscaling by comparing the cutoff ratio to bitrate-specific expectations.

Confidence score (0–100%)

A continuous score based on how far the metrics deviate from the thresholds. Higher confidence means stronger evidence supporting the verdict.

How it differs from the original tcd CLI

Limitations

• Browser audio decoding limits which formats work (depends on AudioContext.decodeAudioData).
• Very short files (< 4096 samples) cannot be analyzed.
• High-bitrate lossy encodes (320 kbps MP3, 256 kbps AAC) may not be distinguishable from lossless by cutoff alone.
• Already-filtered material (e.g. deliberate 15 kHz LPF during mastering) may produce false positives.

References

• Nyquist–Shannon sampling theorem — Wikipedia https://en.wikipedia.org/wiki/Nyquist–Shannon_sampling_theorem
• Equal-loudness contour (Fletcher–Munson curves) — Wikipedia https://en.wikipedia.org/wiki/Equal-loudness_contour
• LAME MP3 encoder psychoacoustic model — Hydrogenaudio Knowledge Base https://wiki.hydrogenaudio.org/index.php?title=LAME
• "Audio Authentication Using Spectral Analysis" — University of Michigan open-access thesis, 2025 https://doi.org/10.7302/28306