diff --git a/core/audio_scan.py b/core/audio_scan.py
index 43eeff0..bc615e8 100644
--- a/core/audio_scan.py
+++ b/core/audio_scan.py
@@ -10,10 +10,14 @@ _SR = 22050
 
 
 def _extract_mfcc(path: str, sr: int = _SR) -> np.ndarray:
-    """Load audio from a file and return a mean MFCC vector (20-dim)."""
+    """Load audio from a file and return an MFCC feature vector (40-dim).
+
+    Concatenates mean + std of each coefficient over time.
+    Mean captures average spectral content; std captures dynamics.
+    """
     y, _ = librosa.load(path, sr=sr, mono=True)
     mfcc = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=_N_MFCC)
-    return mfcc.mean(axis=1)  # average over time → (20,)
+    return np.concatenate([mfcc.mean(axis=1), mfcc.std(axis=1)])
 
 
 def build_profile(clip_paths: list[str]) -> dict | None:
@@ -95,7 +99,7 @@ def scan_video(
 
         chunk = y[pos : pos + win_samples]
         mfcc = librosa.feature.mfcc(y=chunk, sr=sr, n_mfcc=_N_MFCC)
-        vec = mfcc.mean(axis=1)
+        vec = np.concatenate([mfcc.mean(axis=1), mfcc.std(axis=1)])
 
         if mode == "nearest":
             score = max(
diff --git a/tests/test_audio_scan.py b/tests/test_audio_scan.py
index 52e534c..b7961aa 100644
--- a/tests/test_audio_scan.py
+++ b/tests/test_audio_scan.py
@@ -16,7 +16,7 @@ def test_extract_mfcc_returns_1d_vector():
         _make_wav(f.name)
     try:
         vec = _extract_mfcc(f.name)
-        assert vec.shape == (20,)
+        assert vec.shape == (40,)
         assert not np.isnan(vec).any()
     finally:
         os.unlink(f.name)
@@ -29,7 +29,7 @@ def test_build_profile_single_clip():
         profile = build_profile([f.name])
         assert "mean_vector" in profile
         assert "clip_vectors" in profile
-        assert profile["mean_vector"].shape == (20,)
+        assert profile["mean_vector"].shape == (40,)
         assert len(profile["clip_vectors"]) == 1
     finally:
         os.unlink(f.name)
@@ -49,7 +49,7 @@ def test_build_profile_multiple_clips():
 
         profile = build_profile(paths)
         assert len(profile["clip_vectors"]) == 3
-        assert profile["mean_vector"].shape == (20,)
+        assert profile["mean_vector"].shape == (40,)
     finally:
         for p in paths:
             os.unlink(p)