mirror of
https://github.com/openai/whisper.git
synced 2025-11-24 06:26:03 +00:00
13eb8f20d5
- Created whisper/enhancements module for enhanced functionality - Implemented HallucinationDetector with multi-method detection: * Pattern-based detection (YouTube artifacts, repetitive phrases) * Statistical analysis (compression ratios, log probabilities) * Repetition analysis (looping behavior detection) * Temporal analysis (silence-based detection) - Added ConfidenceScorer for comprehensive transcription quality assessment - Enhanced transcribe() function with new parameters: * enhanced_hallucination_detection: Enable advanced detection * hallucination_detection_language: Language-specific patterns * strict_hallucination_filtering: Strict vs permissive filtering * confidence_threshold: Minimum confidence for segments - Maintains full backward compatibility - Added CLI arguments for new functionality Addresses: OpenAI Whisper Discussion #679 - Hallucinations & Repetition Loops
50 lines
1.8 KiB
Python
50 lines
1.8 KiB
Python
#!/usr/bin/env python3
|
|
"""Simple test for enhanced hallucination detection without external dependencies."""
|
|
|
|
import sys
|
|
import os
|
|
|
|
# Test import of the modules
|
|
try:
|
|
sys.path.insert(0, '/Users/safayavatsal/github/OpenSource/whisper')
|
|
|
|
# Test basic imports
|
|
from whisper.enhancements.hallucination_detector import HallucinationDetector
|
|
from whisper.enhancements.confidence_scorer import ConfidenceScorer
|
|
|
|
print("✅ Successfully imported hallucination detection modules")
|
|
|
|
# Test basic functionality
|
|
detector = HallucinationDetector("en")
|
|
print("✅ Created HallucinationDetector instance")
|
|
|
|
# Test pattern detection
|
|
test_text = "Thanks for watching, please subscribe!"
|
|
result = detector.analyze_segment(test_text)
|
|
print(f"✅ Pattern detection test: '{test_text}'")
|
|
print(f" - Detected hallucination: {result.is_hallucination}")
|
|
print(f" - Confidence score: {result.confidence_score:.2f}")
|
|
print(f" - Detected patterns: {result.detected_patterns}")
|
|
|
|
# Test with normal text
|
|
normal_text = "This is a normal conversation about the weather."
|
|
result2 = detector.analyze_segment(normal_text)
|
|
print(f"✅ Normal text test: '{normal_text}'")
|
|
print(f" - Detected hallucination: {result2.is_hallucination}")
|
|
print(f" - Confidence score: {result2.confidence_score:.2f}")
|
|
|
|
# Test confidence scorer
|
|
scorer = ConfidenceScorer("en")
|
|
print("✅ Created ConfidenceScorer instance")
|
|
|
|
print("\n🎉 Basic functionality test completed successfully!")
|
|
print("The enhanced hallucination detection system is working.")
|
|
|
|
except ImportError as e:
|
|
print(f"❌ Import error: {e}")
|
|
sys.exit(1)
|
|
except Exception as e:
|
|
print(f"❌ Unexpected error: {e}")
|
|
import traceback
|
|
traceback.print_exc()
|
|
sys.exit(1) |