Clarity Engine - Hearing Integration

Core Architecture

Input Layer

Audio capture (mic)
Visual gesture (camera)
Tactile sensors
Text input

Processing Core

Multimodal sync
Semantic analysis
Adaptive feedback
Context memory

Output Layer

Speech synthesis
Visual display
Haptic feedback
Text rendering

{
  "system": {
    "name": "ClarityHearingIntegration",
    "version": "1.0",
    "layers": {
      "input": {
        "audio": {
          "sources": ["microphone", "stream"],
          "processors": ["noise_reduction", "fft_analysis"]
        },
        "visual": {
          "sources": ["camera", "screenshare"],
          "processors": ["pose_detection", "sign_language"]
        },
        "tactile": {
          "sources": ["wearables", "touchscreen"],
          "processors": ["pattern_recognition"]
        }
      },
      "sync": {
        "clock": "ntp",
        "tolerance_ms": 50,
        "buffer_strategy": "adaptive"
      },
      "output": {
        "modes": ["audio", "visual", "tactile", "text"],
        "mapping": {
          "frequency_to_color": "hsl(240, 100%, calc(50% + (db * 0.5%)))",
          "speech_to_vibration": "amplitude_modulation"
        }
      }
    }
  }
}

Implementation

Pseudo-Code: Sync Engine

class SyncEngine:
    def __init__(self):
        self.modalities = {}
        self.clock = NTPClock()
        self.buffer = AdaptiveBuffer()
    
    def register(self, modality, callback):
        self.modalities[modality] = {
            'last_ts': 0,
            'callback': callback
        }
    
    def process_frame(self, modality, data):
        current_ts = self.clock.timestamp()
        self.buffer.add(modality, data, current_ts)
        
        # Get synchronized frame bundle
        if self.buffer.ready():
            frame_bundle = self.buffer.pop()
            self.dispatch(frame_bundle)

Pseudo-Code: Haptic Mapper

class HapticMapper:
    def __init__(self):
        self.freq_bands = [125, 250, 500, 1000, 2000, 4000]
        self.actuators = [0, 0, 0, 0, 0, 0]
    
    def map_audio(self, fft_data):
        for i, band in enumerate(self.freq_bands):
            idx = nearest_fft_bin(band)
            self.actuators[i] = fft_data[idx] * sensitivity_curve(band)
        
        return self.normalize(self.actuators)
    
    def normalize(self, values):
        max_val = max(values)
        return [v/max_val if max_val > 0 else 0 for v in values]

Integration Guide

1. Install Dependencies

pip install pyaudio mediapipe numpy

2. Configure Hardware

{
  "audio": {"device_index": 0},
  "haptic": {"com_port": "COM3"}
}

3. Start Services

python -m clarity_hearing --mode=full

Full documentation available in /docs/hearing_integration.md