Mike Swanson
79abef9dc9
- Fix voice_profiler threshold bug (HOST label overwrote Unknown unconditionally) - Audio preload optimization: single ffmpeg per episode, 149.5x realtime on 5070 Ti - WavLM threshold raised to 0.85 (Mike 0.90-0.99, callers 0.46-0.83) - Promo/bumper filter: weighted signature scoring, 42->27 clean Q&A pairs - Text-only Q&A fallback for episodes with no CALLER diarization labels - TRANSFORMERS_OFFLINE=1 to skip HuggingFace freshness checks - Add diarize_2018.py for targeted re-run + FTS5 rebuild - Add benchmark.py + BENCH_SETUP.md for GURU-BEAST-ROG (RTX 4090) comparison - Commit 9-episode training diarization.json outputs - Session log: 2026-04-27-diarization-pipeline.md Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
106 lines
2.9 KiB
Python
106 lines
2.9 KiB
Python
"""
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Audio clip extraction using ffmpeg.
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Cuts clips from original broadcast MP3s for use in Audition/Audacity.
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"""
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import subprocess
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from pathlib import Path
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from rich.console import Console
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console = Console()
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def extract_clip(
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source_path: Path,
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start: float,
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end: float,
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output_path: Path,
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padding: float = 1.5,
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fade_ms: int = 200,
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) -> Path:
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"""
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Extract a clip from source_path between start and end seconds.
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Adds padding on both sides and applies fade in/out.
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Returns the output path.
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"""
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source_path = Path(source_path)
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output_path = Path(output_path)
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output_path.parent.mkdir(parents=True, exist_ok=True)
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clip_start = max(0.0, start - padding)
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clip_end = end + padding
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duration = clip_end - clip_start
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fade_s = fade_ms / 1000.0
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cmd = [
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"ffmpeg", "-y",
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"-ss", f"{clip_start:.3f}",
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"-i", str(source_path),
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"-t", f"{duration:.3f}",
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"-af", f"afade=t=in:st=0:d={fade_s},afade=t=out:st={duration - fade_s:.3f}:d={fade_s}",
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"-q:a", "2",
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str(output_path),
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]
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result = subprocess.run(cmd, capture_output=True, text=True)
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if result.returncode != 0:
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raise RuntimeError(f"ffmpeg failed: {result.stderr[-500:]}")
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return output_path
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def extract_clips_for_results(results, output_dir: Path, padding: float = 1.5) -> dict[int, Path]:
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"""
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Extract clips for a list of QAResult or SearchResult objects.
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Returns {index: clip_path}.
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"""
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output_dir = Path(output_dir)
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clip_paths = {}
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for i, result in enumerate(results):
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episode = result.episode_id
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audio_path = Path(result.audio_path)
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if not audio_path.exists():
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console.print(f"[yellow]Audio not found: {audio_path}[/yellow]")
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continue
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# Determine time range
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if hasattr(result, "question_start"):
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# QAResult
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start = result.question_start
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end = result.answer_end
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else:
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# SearchResult
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start = result.start
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end = result.end
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def fmt(s):
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m, sec = divmod(int(s), 60)
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h, m = divmod(m, 60)
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return f"{h}h{m:02d}m{sec:02d}s" if h else f"{m}m{sec:02d}s"
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clip_name = f"{episode}_{fmt(start)}.mp3"
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clip_path = output_dir / clip_name
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try:
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extract_clip(audio_path, start, end, clip_path, padding=padding)
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clip_paths[i] = clip_path
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console.print(f"[green]Clip {i+1}:[/green] {clip_name}")
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except Exception as e:
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console.print(f"[red]Clip {i+1} failed:[/red] {e}")
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return clip_paths
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def format_timestamp(seconds: float) -> str:
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"""Format seconds as H:MM:SS or M:SS."""
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h = int(seconds // 3600)
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m = int((seconds % 3600) // 60)
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s = int(seconds % 60)
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if h:
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return f"{h}:{m:02d}:{s:02d}"
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return f"{m}:{s:02d}"
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