| |
| |
| """Write the audio front-end reference for `eg2-cli audiocheck`: for every clip of tests/audio/, the Python front end's |
| 16 kHz waveform and log-mel features (raw float32 files in tests/audio/ref/) and tests/audio-preprocess-cases.json |
| with the expected counts and the tolerances the Swift front end must meet. |
| |
| python3 make_audio_preprocess_cases.py [--audio audio] [--out audio-preprocess-cases.json] |
| |
| Tolerances: lossless files decode identically on both sides and the resampler is the same double-precision code, so |
| the waveform must match to 1e-6 (0 for files already at 16 kHz); AAC files decode with the same Apple decoder (1e-6); |
| MP3 files are decoded by libsndfile here (when installed) and by Apple's decoder in Swift, which differ by up to ~3e-5 |
| per sample, which in near-silent frames moves ln(mel + 0.001) by up to ~1 (tolerance 1.0); for the other formats the |
| features must match to 0.02 (the single-precision FFTs of numpy and Accelerate round differently, ~0.005 worst). |
| """ |
| from __future__ import annotations |
|
|
| import argparse |
| import json |
| import sys |
| from pathlib import Path |
|
|
| import numpy as np |
|
|
| HERE = Path(__file__).resolve().parent |
| sys.path.insert(0, str(HERE.parent / "python")) |
| import eg2_audio_frontend as fe |
|
|
|
|
| def main() -> None: |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--audio", default=str(HERE / "audio")) |
| ap.add_argument("--out", default=str(HERE / "audio-preprocess-cases.json")) |
| args = ap.parse_args() |
| audio = Path(args.audio) |
| ref = audio / "ref" |
| ref.mkdir(exist_ok=True) |
| manifest = json.loads((audio / "manifest.json").read_text(encoding="utf-8")) |
| cases = [] |
| for it in manifest: |
| d = fe.decode(audio / it["file"]) |
| wav = fe.resample_16k(fe.to_mono(d.samples), d.sample_rate) |
| inputs = fe.prepare_audio_inputs(wav) |
| feats = fe.log_mel(wav) |
| wave_file = f"ref/{it['name']}.wave16k.f32" |
| feat_file = f"ref/{it['name']}.features.f32" |
| wav.astype("<f4").tofile(audio / wave_file) |
| feats.astype("<f4").tofile(audio / feat_file) |
| is_mp3 = it["file"].endswith(".mp3") |
| cases.append(dict(file=f"audio/{it['file']}", sample_rate=d.sample_rate, channels=int(d.samples.shape[1]), n_samples16k=int(len(wav)), |
| n_frames=inputs.n_frames, n_tokens=inputs.n_tokens, bucket=inputs.bucket, |
| wave_file=f"audio/{wave_file}", features_file=f"audio/{feat_file}", |
| wave_tolerance=1e-4 if is_mp3 else (0.0 if d.sample_rate == 16000 and not it["lossy"] else 1e-6), |
| feature_tolerance=1.0 if is_mp3 else 0.02, python_decoder=d.decoder, |
| note=("mp3: libsndfile (Python) vs Apple (Swift) decoders differ by ~3e-5 per sample" if is_mp3 else None))) |
| print(cases[-1], flush=True) |
| Path(args.out).write_text(json.dumps(cases, indent=1) + "\n", encoding="utf-8") |
| print(f"{len(cases)} cases -> {args.out}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
