# Auditory Processing AGI Component

class AuditoryProcessingAGI:
    def __init__(self):
        # Initialize components
        self.signal_acquisition = SignalAcquisition()
        self.feature_extraction = FeatureExtraction()
        self.cognitive_integration = CognitiveIntegration()

    def process_audio(self, audio_data):
        processed_signal = self.signal_acquisition.process(audio_data)
        features = self.feature_extraction.extract_features(processed_signal)
        response = self.cognitive_integration.integrate(features)
        return response

# Signal Acquisition Component
class SignalAcquisition:
    def __init__(self):
        # Initialization code for acquiring audio signals (e.g., from microphone, file, etc.)
        pass

    def process(self, audio_data):
        # Preprocessing of the audio data: noise reduction, filtering, etc.
        processed_signal = self._preprocess(audio_data)
        return processed_signal

    def _preprocess(self, audio_data):
        # Placeholder for preprocessing steps
        return audio_data  # For simplicity, just returning raw data

# Feature Extraction Component
class FeatureExtraction:
    def __init__(self):
        # Initialization code for feature extraction (e.g., spectrogram, MFCCs)
        pass

    def extract_features(self, processed_signal):
        # Extracting relevant features from the processed signal
        features = self._extract_spectrogram(processed_signal)
        return features

    def _extract_spectrogram(self, audio_data):
        # Placeholder for feature extraction steps
        # In practice, this would involve complex algorithms and possibly machine learning models
        return [1.0]  # For simplicity, just returning a dummy feature vector

# Cognitive Integration Component
class CognitiveIntegration:
    def __init__(self):
        # Initialization code for cognitive integration (e.g., decision-making, context awareness)
        pass

    def integrate(self, features):
        # Integrating the extracted features to form a response
        response = self._make_decision(features)
        return response

    def _make_decision(self, features):
        # Placeholder for decision-making logic
        if features[0] > 0.5:
            return "Recognized speech detected"
        else:
            return "No significant audio activity"

# Main function to test the component
if __name__ == "__main__":
    agi = AuditoryProcessingAGI()
    audio_data = [1, 2, 3, 4, 5]  # Example audio data
    response = agi.process_audio(audio_data)
    print("Response:", response)