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Jarvis AI Assistant - Product Requirements Document (PRD)

1. Product Overview

Jarvis is an advanced AI-powered personal assistant that mimics the functionality of Tony Stark's JARVIS from Iron Man. It features voice recognition, voice cloning, AI-powered responses, and system control capabilities.

2. Core Features

2.1 Voice Recognition and Security

  • Speaker Recognition: Implement voice biometric authentication
  • Wake Word Detection: Activate on hearing "Jarvis"
  • Continuous Listening: Always-on background process
  • Voice Security: Only respond to authorized user's voice

2.2 Voice Interaction

  • Voice Cloning: Clone a specific voice (customizable)
  • Natural Language Processing: Understanding context and intent
  • Real-time Response: Minimal latency in responses
  • Multi-turn Conversations: Remember context of conversations

2.3 AI Integration

  • Large Language Model Integration: Connect to advanced AI models
  • Knowledge Base: Access to vast information resources
  • Learning Capability: Adapt to user preferences over time
  • Context Awareness: Understanding user's patterns and preferences

2.4 System Control

  • Computer Control: Execute system commands via voice
  • Application Control: Launch and manage applications
  • File Management: Navigate and manage files through voice
  • System Settings: Adjust system settings via voice commands

2.5 Information Services

  • Weather Updates: Real-time weather information
  • Web Searches: Internet information retrieval
  • Calendar Integration: Schedule management
  • News Updates: Current events and personalized news

3. Technical Architecture

3.1 Core Components

  • Voice Recognition Engine: For speaker identification and speech-to-text

    • Recommended: Whisper AI for speech recognition
    • Custom voice biometric system for speaker verification

  • Voice Synthesis: For natural speech output

    • Recommended: Coqui TTS or YourTTS for voice cloning

  • AI Backend: For natural language understanding and response generation

    • Recommended: OpenAI GPT-4 or similar LLM

  • System Integration Layer: For computer control and system access

    • Python-based system control modules
    • OS-specific API integrations

3.2 Data Flow

  1. Continuous audio monitoring for wake word
  2. Voice authentication check
  3. Speech-to-text conversion
  4. Intent recognition and processing
  5. AI response generation
  6. Text-to-speech with cloned voice
  7. System command execution (if required)

4. Technical Requirements

4.1 Development Stack

  • Primary Language: Python 3.9+
  • Audio Processing: PyAudio, librosa
  • Machine Learning: PyTorch, TensorFlow
  • Voice Processing: Whisper AI, Coqui TTS
  • System Integration: psutil, pyautogui
  • API Integration: FastAPI/Flask for service integration

4.2 System Requirements

  • Modern multi-core processor (Intel i5/i7 or equivalent)
  • Minimum 16GB RAM
  • GPU support for ML operations
  • High-quality microphone input
  • Stable internet connection
  • Storage: Minimum 20GB free space

5. Security Considerations

  • Voice authentication encryption
  • Secure API key storage
  • Local processing where possible
  • Data privacy compliance
  • Secure system command execution

6. Performance Requirements

  • Wake word detection < 500ms
  • Voice authentication < 1 second
  • Response generation < 2 seconds
  • Voice synthesis < 1 second
  • System command execution < 500ms

7. Future Enhancements

  • Multi-language support
  • Emotion recognition
  • Advanced context awareness
  • IoT device integration
  • Custom skill development platform
  • Mobile app integration

8. Development Phases

Phase 1: Core Foundation

  • Basic voice recognition setup
  • Voice authentication system
  • Basic AI integration
  • Simple system commands

Phase 2: Voice Cloning

  • Voice cloning implementation
  • Natural speech synthesis
  • Conversation memory

Phase 3: Advanced Features

  • Complex system control
  • Advanced AI capabilities
  • Information service integration

Phase 4: Optimization

  • Performance improvements
  • Security enhancements
  • User experience refinement

9. Success Metrics

  • Voice recognition accuracy > 95%
  • Speaker verification accuracy > 99%
  • Response relevance > 90%
  • System command success rate > 99%
  • User satisfaction score > 4.5/5

10. Compliance and Privacy

  • GDPR compliance
  • Data protection measures
  • Transparent data usage
  • User consent management
  • Regular security audits