Update app.py

app.py

@@ -1271,12 +1271,12 @@ class MentorEvaluator:
             features['pitch_mean'] = float(np.mean(valid_f0)) if len(valid_f0) > 0 else 0.0
             features['pitch_std'] = float(np.std(valid_f0)) if len(valid_f0) > 0 else 0.0
             
-            # Rhythm features using hamming window
+            # Rhythm features using window='hann' instead of hamming
             onset_env = librosa.onset.onset_strength(
                 y=audio, 
                 sr=sr,
                 hop_length=hop_length,
-                window='hamming'
+                window='hann'  # Changed from 'hamming' to 'hann'
             )
             tempo, _ = librosa.beat.beat_track(
                 onset_envelope=onset_env,
@@ -1285,13 +1285,13 @@ class MentorEvaluator:
             )
             features['rhythm_regularity'] = float(tempo)
             
-            # Efficient spectral feature extraction with hamming window
+            # Efficient spectral feature extraction with hann window
             mfcc = librosa.feature.mfcc(
                 y=audio, 
                 sr=sr, 
                 n_mfcc=13,
                 hop_length=hop_length,
-                window='hamming'
+                window='hann'  # Changed from 'hamming' to 'hann'
             )
             features['spectral_variance'] = float(np.mean(np.std(mfcc, axis=1)))