# Auditory Processing AGI Component

class AuditoryProcessingAGI:
    def __init__(self):
        self.sensitivity = 0.95
        self.pattern_recognition_threshold = 0.75
        self.noise_reduction_filter = True
        self.signal_to_noise_ratio = 3
        self.sample_rate = 44100
        self.bit_depth = 16
        self.channel_count = 2

    def initialize(self):
        print("Initializing Auditory Processing AGI...")
        # Additional initialization code here

    def process_sound_input(self, sound_data):
        if not self.noise_reduction_filter:
            return "Noise reduction filter is disabled."

        cleaned_signal = self.reduce_noise(sound_data)
        
        if len(cleaned_signal) < 1024:  # Example threshold
            print("Insufficient data to process.")
            return None

        recognized_patterns = self.recognize_patterns(cleaned_signal)

        if not recognized_patterns:
            print("No recognizable patterns detected.")
            return None

        for pattern in recognized_patterns:
            response = self.generate_response(pattern)
            print(f"Recognized pattern: {pattern}, Response: {response}")
        
    def reduce_noise(self, sound_data):
        # Example noise reduction algorithm
        cleaned_signal = [sample / 2 if sample > 100 else 0 for sample in sound_data]
        return cleaned_signal

    def recognize_patterns(self, signal):
        # Simulate pattern recognition using a simple threshold
        patterns = []
        for i in range(len(signal) - 4):  # Assuming each pattern is 5 samples long
            if sum(signal[i:i+5]) > self.signal_to_noise_ratio * len(signal[i:i+5]):
                patterns.append(signal[i])
        return patterns

    def generate_response(self, recognized_pattern):
        response = {
            "0": "Identified voice command: 'Start project'. Initiating task.",
            "1": "Identified noise. Implementing noise reduction algorithms.",
            "2": "Recognized human emotion. Adjusting system for empathy mode."
        }
        return response.get(str(recognized_pattern), "Unknown pattern")

    def feedback_loop(self):
        # Simulate a feedback loop to improve recognition over time
        print("Entering feedback loop to improve recognition accuracy...")
        # Additional code here

# Instantiate and initialize the AGI component
ag_i = AuditoryProcessingAGI()
ag_i.initialize()

# Simulated sound input processing (example)
sound_input = [120, 98, 150, 230, 460, -70, -45, -120, -160, -170] * 10
ag_i.process_sound_input(sound_input)

# Feedback loop (example)
ag_i.feedback_loop()