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
139 lines
4.0 KiB
Python
139 lines
4.0 KiB
Python
#!/usr/bin/env python3
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"""
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Prepare RIR (Room Impulse Response) data for lhotse.
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This script converts rir.scp file to lhotse manifest format.
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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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from typing import List
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from lhotse import CutSet, Recording, SupervisionSegment
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from lhotse.audio import AudioSource
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from lhotse.utils import Pathlike
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def get_args():
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parser = argparse.ArgumentParser(
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description="Prepare RIR data for lhotse",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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)
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parser.add_argument(
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"--rir-scp",
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type=Path,
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required=True,
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help="Path to rir.scp file containing RIR file paths",
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)
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parser.add_argument(
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"--output-dir",
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type=Path,
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required=True,
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help="Output directory for RIR manifests",
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)
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return parser.parse_args()
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def prepare_rir_manifest(
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rir_scp: Pathlike,
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output_dir: Pathlike,
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) -> None:
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"""
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Prepare RIR manifest from rir.scp file.
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Args:
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rir_scp: Path to rir.scp file
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output_dir: Output directory for manifests
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"""
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output_dir = Path(output_dir)
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output_dir.mkdir(parents=True, exist_ok=True)
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recordings = []
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# Read rir.scp file
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with open(rir_scp, 'r') as f:
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for line_idx, line in enumerate(f):
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line = line.strip()
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if not line or line.startswith('#'):
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continue
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# Parse line: either "path" or "id path"
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parts = line.split()
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if len(parts) == 1:
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rir_path = parts[0]
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rir_id = f"rir_{line_idx:06d}"
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elif len(parts) == 2:
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rir_id, rir_path = parts
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else:
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logging.warning(f"Invalid line in rir.scp: {line}")
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continue
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# Check if file exists
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rir_path = Path(rir_path)
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if not rir_path.exists():
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logging.warning(f"RIR file not found: {rir_path}")
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continue
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# Create recording
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recording = Recording(
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id=rir_id,
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sources=[
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AudioSource(
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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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],
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sampling_rate=16000, # Assume 16kHz, will be auto-detected by lhotse
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num_samples=None, # Will be auto-detected
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duration=None, # Will be auto-detected
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)
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recordings.append(recording)
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logging.info(f"Found {len(recordings)} RIR files")
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# Create recording set and save
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from lhotse import RecordingSet
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recording_set = RecordingSet.from_recordings(recordings)
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# Validate recordings (this will auto-detect duration, sampling_rate, etc.)
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logging.info("Validating RIR recordings...")
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recording_set = recording_set.with_path_prefix("") # Ensure absolute paths
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# Save recording manifest
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output_path = output_dir / "rir_recordings.jsonl.gz"
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recording_set.to_file(output_path)
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logging.info(f"Saved RIR recording manifest to {output_path}")
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# Create a simple cuts manifest for RIR (whole files)
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logging.info("Creating RIR cuts manifest...")
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rir_cuts = CutSet.from_manifests(recordings=recording_set)
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cuts_output_path = output_dir / "rir_cuts.jsonl.gz"
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rir_cuts.to_file(cuts_output_path)
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logging.info(f"Saved RIR cuts manifest to {cuts_output_path}")
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return recording_set, rir_cuts
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def main():
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args = get_args()
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logging.basicConfig(
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format="%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s",
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level=logging.INFO,
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)
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logging.info("Preparing RIR data...")
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prepare_rir_manifest(
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rir_scp=args.rir_scp,
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output_dir=args.output_dir,
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)
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logging.info("Done!")
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if __name__ == "__main__":
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main()
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