Add tests

test_audio_processor.py

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+"""Test audio processor module."""
+
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+import numpy as np
+from src.data_processing.audio_processor import AudioProcessor
+
+
+def test_audio_processor_init():
+    """Test AudioProcessor initialization."""
+    processor = AudioProcessor(sample_rate=16000)
+    assert processor.sample_rate == 16000
+    print("✓ AudioProcessor init test passed")
+
+
+def test_normalize_audio():
+    """Test audio normalization."""
+    processor = AudioProcessor()
+    
+    audio = np.array([0.5, -0.5, 1.0, -1.0])
+    normalized = processor.normalize_audio(audio)
+    
+    assert np.abs(normalized).max() <= 1.0
+    print("✓ Normalize audio test passed")
+
+
+def test_remove_silence():
+    """Test silence removal."""
+    processor = AudioProcessor()
+    
+    # Create audio with silence
+    audio = np.concatenate([
+        np.zeros(1000),  # silence
+        np.random.randn(5000),  # speech
+        np.zeros(500),  # silence
+    ])
+    
+    cleaned = processor.remove_silence(audio, threshold_db=40)
+    
+    assert len(cleaned) < len(audio)
+    print("✓ Remove silence test passed")
+
+
+def test_prosody_extraction():
+    """Test prosody feature extraction."""
+    processor = AudioProcessor()
+    
+    # Generate synthetic audio
+    duration = 1.0
+    sample_rate = 16000
+    t = np.linspace(0, duration, int(sample_rate * duration))
+    audio = np.sin(2 * np.pi * 200 * t) * 0.5  # 200Hz tone
+    
+    prosody = processor.extract_prosody_features(audio)
+    
+    assert "mean_pitch" in prosody
+    assert "mean_energy" in prosody
+    print("✓ Prosody extraction test passed")
+
+
+if __name__ == "__main__":
+    test_audio_processor_init()
+    test_normalize_audio()
+    test_remove_silence()
+    test_prosody_extraction()
+    print("\n✅ All audio processor tests passed!")

test_verifier.py

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+"""Test verification module."""
+
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+from src.annotation.automatic_verifier import (
+    AutomaticVerifier,
+    TextLengthRule,
+    SentimentConsistencyRule,
+)
+
+
+def test_verifier_init():
+    """Test verifier initialization."""
+    verifier = AutomaticVerifier()
+    assert len(verifier.rules) > 0
+    print("✓ Verifier init test passed")
+
+
+def test_text_length_rule():
+    """Test text length verification rule."""
+    rule = TextLengthRule(min_length=5, max_length=100)
+    
+    # Test too short
+    passed, msg = rule.verify({"text": "Hi"})
+    assert not passed
+    
+    # Test valid
+    passed, msg = rule.verify({"text": "Valid length text"})
+    assert passed
+    
+    print("✓ Text length rule test passed")
+
+
+def test_sentiment_consistency():
+    """Test sentiment consistency rule."""
+    rule = SentimentConsistencyRule()
+    
+    # Positive text with positive label
+    passed, msg = rule.verify({
+        "text": "ကျေးဇူးပါ",
+        "sentiment": "positive",
+    })
+    assert passed
+    
+    print("✓ Sentiment consistency rule test passed")
+
+
+def test_dataset_verification():
+    """Test full dataset verification."""
+    verifier = AutomaticVerifier()
+    
+    samples = [
+        {"id": "utt_001", "text": "ကျေးဇူးပါ", "sentiment": "positive"},
+        {"id": "utt_002", "text": "မကျေနပ်", "sentiment": "negative"},
+    ]
+    
+    results = verifier.verify_dataset(samples)
+    
+    assert results["total_samples"] == 2
+    assert "statistics" in results
+    
+    print("✓ Dataset verification test passed")
+
+
+def test_sample_filtering():
+    """Test sample filtering based on verification."""
+    verifier = AutomaticVerifier()
+    
+    samples = [
+        {"id": "utt_001", "text": "ကျေးဇူးပါ", "sentiment": "positive"},
+        {"id": "utt_002", "text": "", "sentiment": "negative"},  # Invalid
+    ]
+    
+    kept, removed = verifier.filter_samples(samples)
+    
+    assert len(kept) == 1
+    assert len(removed) == 1
+    
+    print("✓ Sample filtering test passed")
+
+
+if __name__ == "__main__":
+    test_verifier_init()
+    test_text_length_rule()
+    test_sentiment_consistency()
+    test_dataset_verification()
+    test_sample_filtering()
+    print("\n✅ All verifier tests passed!")