mirror of
https://github.com/k2-fsa/icefall.git
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915e8e399c
- Added CHiME-4 dataset integration in asr_datamodule.py - Added Hugging Face upload script - Added RIR augmentation - Added Self-Distillation Training
107 lines
3.3 KiB
Python
107 lines
3.3 KiB
Python
#!/usr/bin/env python3
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"""
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Super simple RIR cuts creator - manual approach without complex lhotse logic
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"""
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import argparse
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import logging
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from pathlib import Path
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import json
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import gzip
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import wave
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import soundfile as sf
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def get_args():
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parser = argparse.ArgumentParser()
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parser.add_argument("--rir-scp", type=Path, required=True)
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parser.add_argument("--output-dir", type=Path, required=True)
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parser.add_argument("--max-files", type=int, default=1000)
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return parser.parse_args()
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def main():
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args = get_args()
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logging.basicConfig(level=logging.INFO)
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args.output_dir.mkdir(parents=True, exist_ok=True)
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recordings = []
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cuts = []
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with open(args.rir_scp, 'r') as f:
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for idx, line in enumerate(f):
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if idx >= args.max_files:
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break
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rir_path = Path(line.strip())
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if not rir_path.exists():
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continue
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try:
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# Use soundfile to get audio info
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info = sf.info(rir_path)
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duration = info.duration
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sampling_rate = info.samplerate
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num_samples = info.frames
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rir_id = f"rir_{idx:06d}"
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# Recording entry - same format as LibriSpeech
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recording = {
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"id": rir_id,
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"sources": [{
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"type": "file",
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"channels": [0],
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"source": str(rir_path.resolve())
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}],
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"sampling_rate": int(sampling_rate),
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"num_samples": int(num_samples),
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"duration": float(duration),
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"channel_ids": [0]
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}
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recordings.append(recording)
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# Cut entry - same format as LibriSpeech
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cut = {
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"id": f"{rir_id}-0",
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"start": 0.0,
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"duration": float(duration),
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"channel": 0,
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"recording_id": rir_id
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}
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cuts.append(cut)
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if (idx + 1) % 100 == 0:
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logging.info(f"Processed {idx + 1} files...")
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except Exception as e:
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logging.warning(f"Failed {rir_path}: {e}")
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continue
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logging.info(f"Created {len(recordings)} recordings and {len(cuts)} cuts")
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# Save files
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rec_path = args.output_dir / "rir_recordings.jsonl.gz"
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with gzip.open(rec_path, 'wt') as f:
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for rec in recordings:
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f.write(json.dumps(rec) + '\n')
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cuts_path = args.output_dir / "rir_cuts.jsonl.gz"
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with gzip.open(cuts_path, 'wt') as f:
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for cut in cuts:
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f.write(json.dumps(cut) + '\n')
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logging.info(f"Saved to {rec_path} and {cuts_path}")
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# Test loading
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try:
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from lhotse import load_manifest
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test_cuts = load_manifest(cuts_path)
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test_recs = load_manifest(rec_path)
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logging.info(f"✓ SUCCESS: {len(test_cuts)} cuts, {len(test_recs)} recordings loaded!")
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except Exception as e:
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logging.error(f"✗ FAILED: {e}")
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if __name__ == "__main__":
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main()
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