diff --git a/normalizer_audios.py b/normalizer_audios.py
index a1df80d6ecbdee5bf64f5712d31f9148043cbd63..d1139f4bb09cef0ef25feb06eb81bc2c39c92cbd 100644
--- a/normalizer_audios.py
+++ b/normalizer_audios.py
@@ -1,32 +1,45 @@
 #!/usr/bin/env python3
 """
-Normalize the energy (RMS level) of all sound event audio files so they
-share a consistent loudness.  This is useful before mixing events into
-background audio at a controlled SNR.
+All-in-one audio processing pipeline for sound event files.
+
+Pipeline:  1) Normalize  ->  2) Trim silence  ->  3) Verify cuts
+
+1. NORMALIZE – scale every file to a target RMS (or peak) level in dBFS
+   so all events share a consistent loudness.
+2. TRIM – remove leading / trailing silence using an energy-based detector
+   with a configurable safety margin.
+3. VERIFY – check every trimmed file for corruption, suspiciously short
+   duration, or abrupt start/end (which would indicate a bad cut).
 
 Usage examples
 --------------
-# Normalize all events to -20 dBFS RMS (default), save to a new folder:
-    python normalize_snr.py
+    # Full pipeline with defaults (in-place, -20 dBFS RMS):
+    python normalizer_audios.py
+
+    # Normalize to -25 dBFS, wider trim margin:
+    python normalizer_audios.py --target-db -25 --margin-ms 50
 
-# Normalize to -25 dBFS RMS:
-    python normalize_snr.py --target-db -25
+    # Peak-normalize instead of RMS:
+    python normalizer_audios.py --mode peak --target-db -1
 
-# Peak-normalize to -1 dBFS instead of RMS:
-    python normalize_snr.py --mode peak --target-db -1
+    # Preview everything without writing:
+    python normalizer_audios.py --dry-run
 
-# Overwrite originals in-place:
-    python normalize_snr.py --inplace
+    # Skip normalization (trim + verify only):
+    python normalizer_audios.py --skip-normalize
 
-# Show per-file stats without writing anything:
-    python normalize_snr.py --dry-run
+    # Skip trimming (normalize + verify only):
+    python normalizer_audios.py --skip-trim
 """
 
 import argparse
-import os
-import sys
 import json
 import logging
+import math
+import os
+import struct
+import sys
+import wave
 from pathlib import Path
 
 import numpy as np
@@ -39,110 +52,101 @@ logging.basicConfig(
 )
 log = logging.getLogger(__name__)
 
-# ── helpers ──────────────────────────────────────────────────────────────────
+AUDIO_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "sound_audios")
+
+# ─────────────────────────────────────────────────────────────────────────────
+# Shared I/O (stdlib wave – used by trimmer & verifier)
+# ─────────────────────────────────────────────────────────────────────────────
+
+def _wav_fmt(sampwidth):
+    if sampwidth == 1:
+        return "B"
+    elif sampwidth == 2:
+        return "h"
+    elif sampwidth == 4:
+        return "i"
+    raise ValueError(f"Unsupported sample width: {sampwidth}")
+
+
+def read_wav_stdlib(filepath):
+    """Read a WAV file with the stdlib *wave* module.
+    Returns (samples_list, sample_rate, sampwidth, nchannels)."""
+    with wave.open(filepath, "rb") as wf:
+        nchannels = wf.getnchannels()
+        sampwidth = wf.getsampwidth()
+        sr = wf.getframerate()
+        nframes = wf.getnframes()
+        raw = wf.readframes(nframes)
+    fmt = _wav_fmt(sampwidth)
+    n_samples = nframes * nchannels
+    samples = list(struct.unpack(f"<{n_samples}{fmt}", raw))
+    return samples, sr, sampwidth, nchannels
+
+
+def write_wav_stdlib(filepath, samples, sr, sampwidth, nchannels):
+    """Write samples to a WAV file with the stdlib *wave* module."""
+    fmt = _wav_fmt(sampwidth)
+    raw = struct.pack(f"<{len(samples)}{fmt}", *samples)
+    with wave.open(filepath, "wb") as wf:
+        wf.setnchannels(nchannels)
+        wf.setsampwidth(sampwidth)
+        wf.setframerate(sr)
+        wf.writeframes(raw)
+
+
+def collect_wav_files(audio_dir):
+    """Return a sorted list of all .wav paths under *audio_dir*."""
+    wav_files = []
+    for root, _dirs, files in os.walk(audio_dir):
+        for f in sorted(files):
+            if f.lower().endswith(".wav"):
+                wav_files.append(os.path.join(root, f))
+    return sorted(wav_files)
+
+
+# ═════════════════════════════════════════════════════════════════════════════
+#  STEP 1 – NORMALIZE
+# ═════════════════════════════════════════════════════════════════════════════
 
 def rms_db(signal: np.ndarray) -> float:
-    """Compute the RMS level of *signal* in dBFS."""
     rms = np.sqrt(np.mean(signal.astype(np.float64) ** 2))
-    if rms == 0:
-        return -np.inf
-    return 20 * np.log10(rms)
+    return -np.inf if rms == 0 else 20 * np.log10(rms)
 
 
 def peak_db(signal: np.ndarray) -> float:
-    """Compute the peak level of *signal* in dBFS."""
     peak = np.max(np.abs(signal.astype(np.float64)))
-    if peak == 0:
-        return -np.inf
-    return 20 * np.log10(peak)
+    return -np.inf if peak == 0 else 20 * np.log10(peak)
 
 
-def normalize(signal: np.ndarray, current_db: float, target_db: float) -> np.ndarray:
-    """Scale *signal* so its level moves from *current_db* to *target_db*."""
+def _apply_gain(signal: np.ndarray, current_db: float, target_db: float) -> np.ndarray:
     if current_db == -np.inf:
-        return signal  # silence – nothing to scale
-    gain_db = target_db - current_db
-    gain_linear = 10 ** (gain_db / 20)
+        return signal
+    gain_linear = 10 ** ((target_db - current_db) / 20)
     out = signal.astype(np.float64) * gain_linear
-    # Soft-clip to prevent digital overs
     peak = np.max(np.abs(out))
     if peak > 1.0:
-        log.warning("Clipping detected (peak %.2f dB), applying limiter.", 20 * np.log10(peak))
+        log.warning("  Clipping detected (peak %.2f dB), applying limiter.", 20 * np.log10(peak))
         out /= peak
     return out
 
-# ── main ─────────────────────────────────────────────────────────────────────
-
-def main():
-    parser = argparse.ArgumentParser(
-        description="Normalize the energy of sound-event WAV files.",
-        formatter_class=argparse.RawDescriptionHelpFormatter,
-    )
-    parser.add_argument(
-        "--input-dir",
-        type=str,
-        default=os.path.join(os.path.dirname(os.path.abspath(__file__)),
-                             "sound_events", "sound_audios"),
-        help="Root directory containing event sub-folders with .wav files.",
-    )
-    parser.add_argument(
-        "--output-dir",
-        type=str,
-        default=None,
-        help="Where to write normalized files (mirrors input structure). "
-             "Defaults to <input_dir>_normalized.",
-    )
-    parser.add_argument(
-        "--inplace",
-        action="store_true",
-        help="Overwrite original files instead of writing to --output-dir.",
-    )
-    parser.add_argument(
-        "--target-db",
-        type=float,
-        default=-20.0,
-        help="Target level in dBFS (default: -20).",
-    )
-    parser.add_argument(
-        "--mode",
-        choices=["rms", "peak"],
-        default="rms",
-        help="Normalization mode: 'rms' (default) or 'peak'.",
-    )
-    parser.add_argument(
-        "--dry-run",
-        action="store_true",
-        help="Only print per-file statistics; do not write any files.",
-    )
-    args = parser.parse_args()
-
-    input_dir = Path(args.input_dir).resolve()
-    if not input_dir.is_dir():
-        log.error("Input directory does not exist: %s", input_dir)
-        sys.exit(1)
 
-    if args.inplace:
-        output_dir = input_dir
-    elif args.output_dir:
-        output_dir = Path(args.output_dir).resolve()
-    else:
-        output_dir = input_dir.parent / (input_dir.name + "_normalized")
+def step_normalize(audio_dir, target_db, mode, dry_run):
+    """Normalize all .wav files in *audio_dir* in-place."""
+    print("\n" + "=" * 70)
+    print("  STEP 1 / 3 — NORMALIZE")
+    print("=" * 70)
 
-    measure_fn = rms_db if args.mode == "rms" else peak_db
-    mode_label = "RMS" if args.mode == "rms" else "Peak"
+    input_dir = Path(audio_dir).resolve()
+    measure_fn = rms_db if mode == "rms" else peak_db
+    mode_label = "RMS" if mode == "rms" else "Peak"
 
-    # Collect all wav files
     wav_files = sorted(input_dir.rglob("*.wav"))
     if not wav_files:
         log.error("No .wav files found under %s", input_dir)
-        sys.exit(1)
+        return
 
-    log.info("Found %d .wav files under %s", len(wav_files), input_dir)
-    log.info("Mode: %s | Target: %.1f dBFS", mode_label, args.target_db)
-    if args.dry_run:
-        log.info("DRY RUN – no files will be written.")
-    else:
-        log.info("Output: %s", output_dir)
+    log.info("Found %d .wav files", len(wav_files))
+    log.info("Mode: %s | Target: %.1f dBFS | dry_run=%s", mode_label, target_db, dry_run)
 
     stats = []
     n_clipped = 0
@@ -150,106 +154,340 @@ def main():
     for wav_path in wav_files:
         rel = wav_path.relative_to(input_dir)
         signal, sr = sf.read(wav_path, dtype="float64")
-
-        # If stereo, measure on the mix-down but keep channels
-        if signal.ndim == 2:
-            mono = signal.mean(axis=1)
-        else:
-            mono = signal
+        mono = signal.mean(axis=1) if signal.ndim == 2 else signal
 
         orig_db = measure_fn(mono)
         orig_peak = peak_db(mono)
-
         entry = {
             "file": str(rel),
             "sr": sr,
             "duration_s": round(len(mono) / sr, 3),
-            f"original_{args.mode}_db": round(orig_db, 2),
+            f"original_{mode}_db": round(orig_db, 2),
             "original_peak_db": round(orig_peak, 2),
         }
 
         if orig_db == -np.inf:
-            log.warning("Skipping silent file: %s", rel)
+            log.warning("  Skipping silent file: %s", rel)
             entry["status"] = "skipped_silent"
             stats.append(entry)
             continue
 
-        # Normalize
-        normed = normalize(signal, orig_db, args.target_db)
-        new_db = measure_fn(normed if normed.ndim == 1 else normed.mean(axis=1))
-        new_peak = peak_db(normed if normed.ndim == 1 else normed.mean(axis=1))
-
+        normed = _apply_gain(signal, orig_db, target_db)
+        new_mono = normed if normed.ndim == 1 else normed.mean(axis=1)
+        new_db = measure_fn(new_mono)
+        new_peak = peak_db(new_mono)
         if new_peak >= 0.0:
             n_clipped += 1
 
-        entry[f"new_{args.mode}_db"] = round(new_db, 2)
+        entry[f"new_{mode}_db"] = round(new_db, 2)
         entry["new_peak_db"] = round(new_peak, 2)
-        entry["gain_db"] = round(args.target_db - orig_db, 2)
+        entry["gain_db"] = round(target_db - orig_db, 2)
         entry["status"] = "ok"
         stats.append(entry)
 
         log.info(
             "%-55s  %s: %+6.1f -> %+6.1f dBFS  (gain %+.1f dB)",
-            str(rel),
-            mode_label,
-            orig_db,
-            new_db,
-            args.target_db - orig_db,
+            str(rel), mode_label, orig_db, new_db, target_db - orig_db,
         )
 
-        if not args.dry_run:
-            dst = output_dir / rel
-            dst.parent.mkdir(parents=True, exist_ok=True)
-            sf.write(str(dst), normed, sr, subtype="PCM_16")
+        if not dry_run:
+            sf.write(str(wav_path), normed, sr, subtype="PCM_16")
 
-    # ── Summary ──────────────────────────────────────────────────────────
-    orig_levels = [s[f"original_{args.mode}_db"] for s in stats
-                   if s["status"] == "ok"]
-    new_levels  = [s[f"new_{args.mode}_db"] for s in stats
-                   if s["status"] == "ok"]
-
-    log.info("─" * 60)
-    log.info("Processed %d / %d files", len(orig_levels), len(wav_files))
+    # Summary
+    orig_levels = [s[f"original_{mode}_db"] for s in stats if s["status"] == "ok"]
+    new_levels  = [s[f"new_{mode}_db"]      for s in stats if s["status"] == "ok"]
 
+    print("-" * 70)
+    log.info("Normalized %d / %d files", len(orig_levels), len(wav_files))
     if orig_levels:
         log.info(
             "Original %s  — min: %.1f  max: %.1f  mean: %.1f  std: %.1f dBFS",
-            mode_label,
-            np.min(orig_levels),
-            np.max(orig_levels),
-            np.mean(orig_levels),
-            np.std(orig_levels),
+            mode_label, np.min(orig_levels), np.max(orig_levels),
+            np.mean(orig_levels), np.std(orig_levels),
         )
         log.info(
             "After norm %s — min: %.1f  max: %.1f  mean: %.1f  std: %.1f dBFS",
-            mode_label,
-            np.min(new_levels),
-            np.max(new_levels),
-            np.mean(new_levels),
-            np.std(new_levels),
+            mode_label, np.min(new_levels), np.max(new_levels),
+            np.mean(new_levels), np.std(new_levels),
         )
     if n_clipped:
         log.warning("%d file(s) required limiting to avoid clipping.", n_clipped)
 
-    # Write stats JSON next to the output
-    if not args.dry_run:
-        stats_path = output_dir / "normalization_stats.json"
+    if not dry_run:
+        stats_path = os.path.join(audio_dir, "normalization_stats.json")
         with open(stats_path, "w") as f:
             json.dump(
-                {
-                    "mode": args.mode,
-                    "target_db": args.target_db,
-                    "n_files": len(wav_files),
-                    "n_processed": len(orig_levels),
-                    "n_clipped": n_clipped,
-                    "files": stats,
-                },
-                f,
-                indent=2,
+                {"mode": mode, "target_db": target_db,
+                 "n_files": len(wav_files), "n_processed": len(orig_levels),
+                 "n_clipped": n_clipped, "files": stats},
+                f, indent=2,
             )
         log.info("Stats written to %s", stats_path)
 
-    log.info("Done.")
+
+# ═════════════════════════════════════════════════════════════════════════════
+#  STEP 2 – TRIM SILENCE
+# ═════════════════════════════════════════════════════════════════════════════
+
+def _to_mono_abs(samples, nchannels, nframes):
+    if nchannels == 1:
+        return [abs(s) for s in samples]
+    mono = []
+    for i in range(nframes):
+        val = sum(abs(samples[i * nchannels + ch]) for ch in range(nchannels))
+        mono.append(val // nchannels)
+    return mono
+
+
+def trim_silence(samples, sr, nchannels, threshold_ratio=0.02,
+                 margin_ms=30, frame_ms=10):
+    """Return (trimmed_samples, original_ms, new_ms)."""
+    nframes = len(samples) // nchannels
+    mono = _to_mono_abs(samples, nchannels, nframes)
+
+    peak = max(mono) if mono else 0
+    if peak == 0:
+        dur = nframes / sr * 1000
+        return samples, dur, dur
+
+    threshold = peak * threshold_ratio
+    frame_len = max(1, int(sr * frame_ms / 1000))
+    hop = max(1, frame_len // 2)
+
+    first_loud = last_loud = None
+    pos = 0
+    while pos + frame_len <= nframes:
+        window = mono[pos:pos + frame_len]
+        rms = math.sqrt(sum(s * s for s in window) / frame_len)
+        if rms > threshold:
+            if first_loud is None:
+                first_loud = pos
+            last_loud = pos + frame_len
+        pos += hop
+
+    if first_loud is None:
+        dur = nframes / sr * 1000
+        return samples, dur, dur
+
+    margin_samp = int(sr * margin_ms / 1000)
+    start = max(0, first_loud - margin_samp)
+    end = min(nframes, last_loud + margin_samp)
+
+    trimmed = samples[start * nchannels : end * nchannels]
+    return trimmed, nframes / sr * 1000, (end - start) / sr * 1000
+
+
+def step_trim(audio_dir, threshold_ratio, margin_ms, dry_run):
+    """Trim leading/trailing silence from every .wav in *audio_dir*."""
+    print("\n" + "=" * 70)
+    print("  STEP 2 / 3 — TRIM SILENCE")
+    print("=" * 70)
+
+    wav_files = collect_wav_files(audio_dir)
+    if not wav_files:
+        log.error("No .wav files found in %s", audio_dir)
+        return
+
+    log.info("Found %d .wav files", len(wav_files))
+    log.info("Settings: threshold=%.3f, margin=%gms, dry_run=%s",
+             threshold_ratio, margin_ms, dry_run)
+    print("-" * 70)
+
+    total_saved = 0
+    trimmed_count = 0
+
+    for i, fpath in enumerate(wav_files, 1):
+        rel = os.path.relpath(fpath, audio_dir)
+        try:
+            samples, sr, sw, nch = read_wav_stdlib(fpath)
+        except Exception as e:
+            log.error("[%d/%d] ERROR reading %s: %s", i, len(wav_files), rel, e)
+            continue
+
+        trimmed, orig_ms, new_ms = trim_silence(
+            samples, sr, nch, threshold_ratio, margin_ms)
+        saved = orig_ms - new_ms
+
+        if saved > 1:
+            trimmed_count += 1
+            total_saved += saved
+            tag = "DRY-RUN" if dry_run else "TRIMMED"
+            log.info("[%d/%d] %s %s: %dms -> %dms (cut %dms)",
+                     i, len(wav_files), tag, rel,
+                     int(orig_ms), int(new_ms), int(saved))
+            if not dry_run:
+                write_wav_stdlib(fpath, trimmed, sr, sw, nch)
+        else:
+            log.info("[%d/%d] OK      %s: %dms (no silence)",
+                     i, len(wav_files), rel, int(orig_ms))
+
+    print("-" * 70)
+    log.info("Trimmed %d/%d files, saved %.1fs total.",
+             trimmed_count, len(wav_files), total_saved / 1000)
+
+
+# ═════════════════════════════════════════════════════════════════════════════
+#  STEP 3 – VERIFY CUTS
+# ═════════════════════════════════════════════════════════════════════════════
+
+MIN_DURATION_MS = 50
+EDGE_CHECK_MS = 5
+EDGE_AMPLITUDE_RATIO = 0.5
+
+
+def _check_one_file(filepath, audio_dir):
+    """Return (duration_ms, [warnings])."""
+    warnings = []
+    try:
+        samples, sr, sw, nch = read_wav_stdlib(filepath)
+    except Exception as e:
+        return 0, [f"CORRUPT: {e}"]
+
+    nframes = len(samples) // nch
+    dur = nframes / sr * 1000
+
+    if nframes == 0:
+        return 0, ["EMPTY: 0 frames"]
+
+    if dur < MIN_DURATION_MS:
+        warnings.append(f"VERY SHORT: {dur:.0f}ms (< {MIN_DURATION_MS}ms)")
+
+    mono = _to_mono_abs(samples, nch, nframes)
+    peak = max(mono) if mono else 0
+    if peak == 0:
+        warnings.append("SILENT: completely silent")
+        return dur, warnings
+
+    edge_n = max(1, int(sr * EDGE_CHECK_MS / 1000))
+
+    start_max = max(mono[:edge_n])
+    if start_max > peak * EDGE_AMPLITUDE_RATIO:
+        warnings.append(
+            f"ABRUPT START: first {EDGE_CHECK_MS}ms at "
+            f"{start_max/peak*100:.0f}% of peak")
+
+    end_max = max(mono[-edge_n:])
+    if end_max > peak * EDGE_AMPLITUDE_RATIO:
+        warnings.append(
+            f"ABRUPT END: last {EDGE_CHECK_MS}ms at "
+            f"{end_max/peak*100:.0f}% of peak")
+
+    return dur, warnings
+
+
+def step_verify(audio_dir):
+    """Verify all trimmed .wav files for quality issues."""
+    print("\n" + "=" * 70)
+    print("  STEP 3 / 3 — VERIFY CUTS")
+    print("=" * 70)
+
+    wav_files = collect_wav_files(audio_dir)
+    if not wav_files:
+        log.error("No .wav files found in %s", audio_dir)
+        return
+
+    log.info("Verifying %d .wav files", len(wav_files))
+    print("-" * 70)
+
+    flagged = []
+    total_dur = 0
+
+    for i, fpath in enumerate(wav_files, 1):
+        rel = os.path.relpath(fpath, audio_dir)
+        dur, warns = _check_one_file(fpath, audio_dir)
+        total_dur += dur
+        if warns:
+            flagged.append((rel, dur, warns))
+            log.warning("[%d/%d] WARNING %s (%dms)", i, len(wav_files), rel, int(dur))
+            for w in warns:
+                log.warning("           -> %s", w)
+        else:
+            log.info("[%d/%d] OK      %s (%dms)", i, len(wav_files), rel, int(dur))
+
+    print("=" * 70)
+    log.info("Total files: %d | Duration: %.1fs", len(wav_files), total_dur / 1000)
+    log.info("Files OK: %d | Flagged: %d", len(wav_files) - len(flagged), len(flagged))
+
+    if flagged:
+        print("\n--- FLAGGED FILES (review manually) ---")
+        for rel, dur, warns in flagged:
+            print(f"\n  {rel} ({dur:.0f}ms):")
+            for w in warns:
+                print(f"    - {w}")
+    else:
+        print("\nAll files look good!")
+
+
+# ═════════════════════════════════════════════════════════════════════════════
+#  MAIN
+# ═════════════════════════════════════════════════════════════════════════════
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Audio pipeline: Normalize -> Trim silence -> Verify cuts",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+    )
+
+    # General
+    parser.add_argument(
+        "--audio-dir", type=str, default=AUDIO_DIR,
+        help="Root directory containing event sub-folders with .wav files "
+             f"(default: {AUDIO_DIR})",
+    )
+    parser.add_argument(
+        "--dry-run", action="store_true",
+        help="Preview all steps without writing any files.",
+    )
+
+    # Normalize options
+    norm = parser.add_argument_group("Normalization (step 1)")
+    norm.add_argument("--skip-normalize", action="store_true",
+                      help="Skip the normalization step.")
+    norm.add_argument("--target-db", type=float, default=-20.0,
+                      help="Target level in dBFS (default: -20).")
+    norm.add_argument("--mode", choices=["rms", "peak"], default="rms",
+                      help="Normalization mode (default: rms).")
+
+    # Trim options
+    trim = parser.add_argument_group("Trimming (step 2)")
+    trim.add_argument("--skip-trim", action="store_true",
+                      help="Skip the silence trimming step.")
+    trim.add_argument("--threshold", type=float, default=0.02,
+                      help="Silence threshold as fraction of peak (default: 0.02).")
+    trim.add_argument("--margin-ms", type=float, default=30,
+                      help="Margin in ms to keep around the sound (default: 30).")
+
+    # Verify options
+    verify = parser.add_argument_group("Verification (step 3)")
+    verify.add_argument("--skip-verify", action="store_true",
+                        help="Skip the verification step.")
+
+    args = parser.parse_args()
+    audio_dir = args.audio_dir
+
+    log.info("Audio directory: %s", audio_dir)
+
+    # ── Step 1 ──
+    if not args.skip_normalize:
+        step_normalize(audio_dir, args.target_db, args.mode, args.dry_run)
+    else:
+        log.info("Skipping normalization (--skip-normalize).")
+
+    # ── Step 2 ──
+    if not args.skip_trim:
+        step_trim(audio_dir, args.threshold, args.margin_ms, args.dry_run)
+    else:
+        log.info("Skipping trimming (--skip-trim).")
+
+    # ── Step 3 ──
+    if not args.skip_verify:
+        step_verify(audio_dir)
+    else:
+        log.info("Skipping verification (--skip-verify).")
+
+    print("\n" + "=" * 70)
+    log.info("Pipeline complete.")
+    print("=" * 70)
 
 
 if __name__ == "__main__":
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