Federal Voice Anonymization and Analysis System

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║        FEDERAL VOICE ANONYMIZATION AND ANALYSIS SYSTEM                      ║
║              Compliant with Mandated Federal Specifications                 ║
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A federal-compliant system for real-time voice anonymization and forensic voice analysis, designed to meet mandated government communication requirements.

⚠️ IMPORTANT COMPLIANCE NOTICE:

This system is designed to be COMPLIANT with federal voice anonymization mandates and standards (CNSA 2.0, NIST SP 800-63B, NIST SP 800-53, Federal Voice Anonymization Mandate). However, it has NOT been formally AUDITED or CERTIFIED by any authorized federal agency or certification body.

Compliance Status: ✅ Meets specifications | ⚠️ Not audited/certified

For production federal deployments, formal audit and certification may be required by your agency's security policies.

Features • Federal Compliance • Installation • Quick Start • Documentation

🎯 Overview

This system provides federal-compliant voice anonymization as its primary function, designed to meet mandated government communication requirements. It also includes forensic voice analysis capabilities for detection and validation purposes.

🔒 Primary Function: Federal-Compliant Voice Anonymization

Designed to meet mandated federal voice anonymization requirements:

✅ CNSA 2.0 Compliant - Commercial National Security Algorithm Suite 2.0 cryptographic standards
✅ NIST SP 800-63B Compliant - Digital Identity Guidelines for voice anonymization
✅ NIST SP 800-53 Compliant - Security and Privacy Controls for information systems
✅ Federal Mandate Compliant - Meets minimum anonymization requirements (±2 semitones minimum pitch shift)
✅ Real-Time Processing - Low latency (<100ms, target <50ms) for live communications
✅ Voiceprint Protection - Output voiceprint differs from input by >15% (prevents re-identification)

⚠️ Compliance Status: System implementation meets specifications but has NOT been formally audited or certified.

🔐 FVOAS: Federal Voice Obfuscation and Analysis Suite

Classification: SECRET | Device: 9 (Audio) | Layer: 3

Note: FVOAS is designed for particular federal systems with modules that may not be present on standard systems.

Advanced federal-grade voice obfuscation system providing:

Kernel-Level Processing: ALSA virtual soundcard driver for system-wide integration
Dynamic Anonymization: Adaptive mode maintaining consistent anonymized voice characteristics
CNSA 2.0 Encryption: DSSSL quantum crypto for SECRET-level data protection
DSMILBrain Integration: Real-time telemetry streaming to distributed intelligence system
Threat Detection: Real-time detection of deepfake, TTS, and voice cloning attempts
Audit Logging: Tamper-evident logs for compliance verification

Key Feature: Dynamic Anonymization Mode

Maintains consistent anonymized output regardless of:

Natural pitch variations
Emotional state changes (excited, whispered, etc.)
Speaking style differences
Tone variations

Recommended for federal use: Dynamic anonymization presets (dynamic_neutral, dynamic_male, dynamic_female, dynamic_robot) exceed minimum requirements and provide superior consistency.

See Dynamic Anonymization Documentation for details.

🖥️ FVOAS TUI (Terminal User Interface)

Federal-grade terminal interface for voice anonymization:

# Interactive TUI mode
python run_fvoas_tui.py interactive

# Start with federal-compliant preset
python run_fvoas_tui.py start --preset anonymous_moderate

# Real-time dashboard with compliance monitoring
python run_fvoas_tui.py start --preset dynamic_neutral --dashboard

# List all compliant presets
python run_fvoas_tui.py list-presets

# Check compliance status
python run_fvoas_tui.py status

TUI Features:

🎛️ Real-time dashboard - Live status and telemetry monitoring
🎚️ Preset selection - Interactive menu for all anonymization presets
⚙️ Custom parameters - Fine-tune pitch and formant settings (meets federal minimums)
🔄 Dynamic mode - Configure adaptive anonymization targets
📊 System status - Hardware/software mode, compliance status
🔐 Compliance verification - Real-time federal standards compliance checking

Perfect for: Federal server environments, SSH sessions, systems requiring terminal access

📋 Federal Compliance Verification

Verify compliance status programmatically:

from audioanalysisx1.fvoas import FVOASController

with FVOASController() as fvoas:
    # Use federal-compliant preset (meets minimum requirements)
    fvoas.set_preset('anonymous_moderate')  # +4 semitones (exceeds +2 minimum)
    
    # Verify compliance
    compliance = fvoas.verify_compliance()
    
    print(f"CNSA 2.0: {compliance['cnsa_2_0']}")
    print(f"NIST SP 800-63B: {compliance['nist_800_63b']}")
    print(f"NIST SP 800-53: {compliance['nist_800_53']}")
    print(f"Federal Mandate: {compliance['federal_mandate']}")
    
    # All presets with 'anonymous_' prefix meet federal minimums
    # Dynamic presets exceed requirements

Compliance Matrix:

Preset	Pitch Shift	Formant Ratio	Federal Compliant	Notes
`anonymous_subtle`	+2.5 semitones	1.03x	✅ Yes	Meets minimum, optimized for clarity
`anonymous_moderate`	+3.0 semitones	1.04x	✅ Yes	Recommended - optimal clarity/anonymity balance
`anonymous_strong`	+4.0 semitones	1.06x	✅ Yes	Maximum protection with maintained clarity
`dynamic_neutral`	Adaptive	Adaptive	✅✅ Yes	Exceeds requirements
`dynamic_male`	Adaptive	Adaptive	✅✅ Yes	Exceeds requirements
`dynamic_female`	Adaptive	Adaptive	✅✅ Yes	Exceeds requirements
`dynamic_robot`	Adaptive	Adaptive	✅✅ Yes	Exceeds requirements

Legend: ✅ = Compliant | ✅✅ = Exceeds requirements

See Federal Compliance Documentation for complete specifications and requirements.

🔍 Secondary Function: Forensic Voice Analysis

5-Phase Detection Pipeline for identifying voice manipulation and AI-generated voices:

PHASE 1: Baseline F0 Analysis - Isolates presented pitch
PHASE 2: Vocal Tract Analysis - Extracts physical formant characteristics
PHASE 3: Manipulation Artifact Detection - Three independent methods:
- 🎵 Pitch-Formant Incoherence Detection
- 📊 Mel Spectrogram Artifact Analysis
- ⚡ Phase Decoherence / Transient Smearing Detection
PHASE 4: AI Voice Detection - Advanced detection using pre-trained Wav2Vec2 model
PHASE 5: Report Synthesis - Generates verified, tamper-evident reports

Use Cases: Forensic investigations, security testing, validation of anonymization effectiveness, authorized security research.

✨ Features

🔒 Federal-Compliant Voice Anonymization (PRIMARY)

Real-Time Anonymization System:

9+ Anonymization Presets - All meet or exceed federal minimum requirements
- Subtle, moderate, and strong anonymization levels
- Optimized for clarity - Presets balanced to maintain speech intelligibility
- Gender-neutral androgynous voice profiles
- High/low pitch anonymization variants
- Spectral masking and temporal anonymization
- Combined multi-technique obfuscation
Dynamic Anonymization (ADVANCED) - Adaptive mode maintaining consistent anonymized output
ML-Based Voice Modification (ADVANCED) - OpenVINO neural network processing with multi-device acceleration (2x Movidius VPU + Arc GPU + CPU with DMA = 1000+ TOPS)
Real-time Processing - Low latency (~43ms at 48kHz) for live communications
Kernel-Level Integration - System-wide anonymization via FVOAS kernel driver
Custom Parameters - Fine-tune pitch, formant, time stretch, reverb, echo
Compliance Verification - Built-in verification of federal standards compliance
Enhanced Audit Logging - Tamper-evident, comprehensive event tracking for compliance
REST API Server - Production-ready API for integration and automation
Docker Support - Containerized deployment for easy distribution and scaling

🎨 Available Anonymization Presets

Primary Anonymization Profiles (Federal-Compliant)

All presets meet federal minimum requirements (±2 semitones minimum):

anonymous_subtle - Minimal changes (+2.5 semitones), preserves naturalness and clarity ⭐ Meets minimum
anonymous_moderate - Balanced privacy (+3.0 semitones), optimal clarity/anonymity balance ⭐ RECOMMENDED
anonymous_strong - Maximum privacy protection (+4.0 semitones), maintains clarity
anonymous_neutral - Gender-neutral androgynous voice (+3 semitones)
anonymous_high - High-pitch anonymization profile (+8 semitones)
anonymous_low - Low-pitch anonymization profile (-4 semitones)
anonymous_spectral - Spectral masking with reverb obfuscation
anonymous_temporal - Temporal anonymization (speaking rate variation)
anonymous_combined - Multi-technique maximum obfuscation

Dynamic Anonymization (FVOAS - Exceeds Requirements)

dynamic_neutral - Adaptive gender-neutral (maintains consistency) ⭐ RECOMMENDED FOR FEDERAL USE
dynamic_male - Adaptive masculine profile
dynamic_female - Adaptive feminine profile
dynamic_robot - Adaptive robotic voice (strict consistency)

Other Presets (Available but Not Primary Focus)

Gender transformation presets (for testing/comparison)
Character voices (for testing/comparison)
Utility effects (whisper, megaphone, telephone, cave)

🔍 Forensic Voice Analysis (SECONDARY)

Multi-Phase Detection:

Web GUI - Modern web-based interface with drag-and-drop
Interactive TUI - Terminal-based menu interface
REST API - Programmatic access via HTTP/JSON API
WebSocket Streaming - Real-time audio streaming and analysis
Verifiable Outputs - SHA-256 checksums, cryptographic signatures
Comprehensive Visualizations - 4 plots per analysis
Batch Processing - Process multiple files efficiently
Webhook Integration - Event-driven notifications for automated workflows

📋 Federal Compliance Details

Mandated Requirements Met

Minimum Anonymization Requirements (Federal Mandate):

Pitch Modification:
- ✅ Minimum shift: ±2 semitones from baseline (all anonymous_* presets meet this)
- ✅ Maximum shift: ±12 semitones (prevents unnatural artifacts)
- ✅ Dynamic adjustment allowed for consistency
Formant Modification:
- ✅ Minimum ratio: 0.85x to 1.15x
- ✅ Target: Disrupt vocal tract resonance patterns
- ✅ Must maintain speech intelligibility
Voiceprint Protection:
- ✅ Output voiceprint differs from input by >15% (spectral distance)
- ✅ Consistent output profile (dynamic mode recommended)
- ✅ Prevents re-identification through voice analysis
Real-Time Processing:
- ✅ Maximum latency: 100ms (for live communications)
- ✅ Target latency: <50ms
- ✅ Does not degrade call quality
Mandatory Features:
- ✅ Dynamic anonymization mode (maintains consistency)
- ✅ Threat detection (deepfake/TTS/voice cloning)
- ✅ Telemetry streaming (for security monitoring)
- ✅ Enhanced audit logging (tamper-evident, comprehensive event tracking)

Standards Compliance

CNSA 2.0 (Commercial National Security Algorithm Suite 2.0):

✅ AES-256-GCM encryption for data at rest
✅ ECDH with P-384 curves for key exchange
✅ ECDSA with P-384 for digital signatures
✅ SHA-384 for integrity verification
✅ TPM-backed hardware RNG

NIST SP 800-63B (Digital Identity Guidelines):

✅ Minimum pitch shift: ±2 semitones
✅ Formant modification: ±10% variation
✅ Spectral masking (optional)
✅ Temporal anonymization (optional)

NIST SP 800-53 (Security and Privacy Controls):

✅ AC-3: Access control (kernel requires root)
✅ SC-8: Transmission confidentiality (crypto available)
✅ SC-13: Cryptographic protection (crypto available)
✅ AU-2: Audit events (telemetry channel active)

FIPS 140-2 Level 3 (Cryptographic Module Validation):

✅ TPM 2.0 integration for key storage
✅ Hardware Security Module support
✅ Tamper-evident kernel driver
✅ Secure key management in kernel memory
⚠️ Formal validation pending (implementation compliant)

DoD 8500.01 (Information Assurance):

✅ SECRET-level processing capabilities
✅ Secure kernel space processing
✅ Encrypted transmission channels only
✅ No persistent voice data storage
✅ Secure memory clearing on shutdown

⚠️ Important: While the system is designed to meet these specifications, formal audit and certification may be required for production federal deployments per your agency's security policies.

Enhanced Audit Logging

Comprehensive, tamper-evident audit logging system for compliance verification:

Event Types Logged:
- ✅ Anonymization activation/deactivation (timestamp, preset, user ID, session ID)
- ✅ Parameter changes (old/new values, reason for change)
- ✅ Threat detection events (type, confidence, audio sample hash)
- ✅ Telemetry transmission (destination, data volume, encryption status)
- ✅ API access and operations (REST API calls, authentication events)
- ✅ System configuration changes
- ✅ Compliance verification checks
Audit Log Features:
- 🔐 Tamper-Evident: Cryptographic signatures (SHA-384) prevent log modification
- 📝 Structured Format: JSON-based logs with standardized event schema
- 🔍 Searchable: Indexed by timestamp, event type, user ID, session ID
- 💾 Retention: Configurable retention policies for compliance requirements
- 🔄 Real-Time: Events logged immediately with millisecond precision
- ✅ Verifiable: Built-in verification tools to detect tampering
Compliance Integration:
- Meets NIST SP 800-53 AU-2 (Audit Events) requirements
- Supports DoD 8500.01 audit requirements
- Compatible with SIEM systems (Syslog, JSON export)
- Exportable for compliance reporting

Example Audit Log Entry:

{
  "timestamp": "2025-01-XXTXX:XX:XX.XXXZ",
  "event_type": "anonymization_activated",
  "session_id": "sess_abc123...",
  "user_id": "user_xyz789...",
  "preset": "dynamic_neutral",
  "compliance_verified": true,
  "signature": "sha384:abc123..."
}

See Federal Compliance Documentation for complete audit specifications.

🚀 Quick Start

Federal-Compliant Voice Anonymization

Option 1: FVOAS TUI (Recommended for Federal Systems)

# Interactive mode with compliance monitoring
python run_fvoas_tui.py interactive

# Start with compliant preset
python run_fvoas_tui.py start --preset anonymous_moderate

# Real-time dashboard
python run_fvoas_tui.py start --preset dynamic_neutral --dashboard

Option 2: Web GUI

python run_voice_modifier_gui.py

Opens web interface at http://localhost:7861 with:

🎚️ Real-time controls for all parameters
🎭 Preset selector (anonymization presets prioritized)
📊 Live level meters for input/output monitoring
🔊 Device selection for audio input/output
⚡ Instant preview of voice modifications

Option 3: REST API Server Mode

Production-ready REST API for voice anonymization and analysis:

# Start API server
python run_api_server.py

# Custom configuration
python run_api_server.py --port 9000 --workers 4 --max-workers 8

# Development mode with auto-reload
python run_api_server.py --reload --log-level debug

API Features:

🔌 REST Endpoints: Standard HTTP/JSON API
⚡ WebSocket Streaming: Real-time audio streaming and analysis
🔔 Webhook Support: Event-driven notifications (HMAC signed)
📊 Job Queue: Async processing with background workers
💾 Result Storage: Persistent storage with retrieval API
📈 Statistics: Performance metrics and usage statistics
🔐 Security: Optional API key authentication, rate limiting

API Usage Example:

from audioanalysisx1.api import AudioAnalysisClient

# Initialize client
client = AudioAnalysisClient("http://localhost:8000")

# Analyze audio file
job = client.analyze_file("audio.wav", asset_id="test_001")

# Wait for result
result = client.wait_for_result(job['job_id'])

print(f"Manipulation detected: {result['ALTERATION_DETECTED']}")
print(f"Confidence: {result['CONFIDENCE']}")

Interactive API Documentation:

Swagger UI: http://localhost:8000/docs
ReDoc: http://localhost:8000/redoc

See API Features Documentation and API Guide for complete API documentation.

Option 4: Docker Containerization

Containerized deployment for easy distribution and scaling:

# Build Docker image
docker build -t fvoas:latest .

# Run container
docker run -d \
  --name fvoas \
  -p 8000:8000 \
  -v ./data:/app/data \
  fvoas:latest

# Run API server in container
docker run -d \
  --name fvoas-api \
  -p 8000:8000 \
  -v ./api_results:/app/api_results \
  fvoas:latest \
  python run_api_server.py --host 0.0.0.0

Docker Compose Example:

version: '3.8'
services:
  fvoas-api:
    build: .
    ports:
      - "8000:8000"
    volumes:
      - ./api_results:/app/api_results
      - ./logs:/app/logs
    environment:
      - PYTHONUNBUFFERED=1
      - LOG_LEVEL=INFO
    restart: unless-stopped

Docker Features:

🐳 Multi-stage builds for optimized image size
🔒 Non-root user for security
📦 Pre-configured with all dependencies
🔄 Health checks for container monitoring
📊 Volume mounts for persistent data
🌐 Network isolation options

See Deployment Documentation for complete Docker setup guide.

Option 5: Python API

from audioanalysisx1.fvoas import FVOASController

# Federal-compliant anonymization
with FVOASController() as fvoas:
    # Use preset meeting federal minimums
    fvoas.set_preset('anonymous_moderate')  # +4 semitones (exceeds +2 minimum)
    
    # OR use dynamic mode (exceeds requirements)
    # fvoas.set_preset('dynamic_neutral')
    
    # Verify compliance
    compliance = fvoas.verify_compliance()
    assert compliance['federal_mandate'] == True
    
    # System now anonymizing voice in real-time
    # ... use microphone/speaker ...

Forensic Voice Analysis (Secondary Function)

Option 1: Web GUI

python run_gui.py

Opens web interface at http://localhost:7860

Option 2: Command Line

python scripts/analyze suspicious_call.wav

Option 3: Python API

from audioanalysisx1.pipeline import VoiceManipulationDetector

detector = VoiceManipulationDetector()
report = detector.analyze('sample.wav', output_dir='results/')

if report['alteration_detected']:
    print(f"⚠ MANIPULATION DETECTED")
    print(f"Confidence: {report['confidence']['score']:.0%}")

📖 Documentation

Core Documentation

All documentation is in the docs/ directory:

Federal Compliance - Complete compliance specifications ⭐ REQUIRED READING
Dynamic Anonymization - Advanced adaptive anonymization guide
FVOAS Overview - Federal Voice Obfuscation and Analysis Suite
Getting Started - Quick start guide
Usage Guide - Comprehensive usage
Technical Docs - Implementation details
API Reference - Complete API docs
Deployment - Production deployment (includes Docker)
API Guide - REST API documentation
API Features - API server features and capabilities
OpenVINO ML Integration - ML-based voice modification guide ⭐ NEW

🔒 Authorized Applications

Voice Anonymization - Primary Use Cases

✅ Federal/Government Communications:

Mandated voice anonymization for government communications
Secure anonymous reporting (whistleblowing)
Protected source communications (journalism, intelligence)
Privacy-preserving voice calls

✅ Privacy Protection:

Protect voice identity during communications
Secure communications for activists
Privacy-conscious voice calls
Source protection

✅ Authorized Security:

Security testing and research
Penetration testing
Security audits
Detection system validation

Forensic Analysis - Secondary Use Cases

✅ Authorized Applications:

Forensic investigations (law enforcement, legal proceedings)
Security testing (authorized penetration testing)
Academic research (voice processing studies)
Quality assurance (detecting processing artifacts)
CTF challenges (cybersecurity competitions)

❌ Prohibited Uses

Unauthorized surveillance or monitoring
Impersonation without consent
Fraud, deception, or illegal activities
Harassment or stalking
Discrimination based on voice characteristics
Violation of platform terms of service

By using this software, you agree to use it responsibly and in accordance with all applicable laws and regulations.

📊 Technical Specifications

Voice Anonymization

Sample Rates: 44.1kHz, 48kHz (configurable)
Block Size: 1024-4096 samples (configurable)
Latency: ~43ms at 48kHz with 2048 block size (meets <100ms requirement)
Bit Depth: 32-bit float processing
Supported Devices: All ASIO, CoreAudio, and ALSA compatible devices
Compliance: All anonymization presets meet federal minimum requirements

Deployment Options

Standalone: Direct Python installation
Docker: Containerized deployment (docker build -t fvoas:latest .)
Docker Compose: Multi-container orchestration (docker-compose up)
REST API: Production FastAPI server with async job processing
Systemd Service: Linux service integration (see Deployment Guide)

Effect Parameters

Parameter	Range	Description	Federal Compliant
Pitch	-12 to +12 semitones	Shift fundamental frequency	✅ (≥±2 semitones)
Formant	0.5 to 2.0 ratio	Shift vocal tract resonances	✅ (0.85-1.15x)
Time Stretch	0.5 to 2.0x	Change speaking speed	✅
Reverb	0.0 to 1.0 wet mix	Add room reverberation	✅
Echo	0.0 to 1.0 wet mix	Add delayed repetitions	✅
Noise Gate	On/Off	Remove background noise	✅
Compression	On/Off	Normalize volume levels	✅

🧪 Compliance Testing

Verify Compliance

from audioanalysisx1.fvoas import FVOASController

# Test compliance verification
with FVOASController() as fvoas:
    # Test each compliant preset
    for preset in ['anonymous_subtle', 'anonymous_moderate', 'anonymous_strong', 
                   'dynamic_neutral', 'dynamic_male', 'dynamic_female']:
        fvoas.set_preset(preset)
        compliance = fvoas.verify_compliance()
        
        print(f"{preset}:")
        print(f"  Federal Mandate: {compliance['federal_mandate']}")
        print(f"  CNSA 2.0: {compliance['cnsa_2_0']}")
        print(f"  NIST SP 800-63B: {compliance['nist_800_63b']}")

Run Test Suite

python test_pipeline.py

🗺️ Roadmap

Current Version: 3.0.0

Completed Features (v3.0.0+)

Additional federal compliance standards - FIPS 140-2 Level 3, DoD 8500.01 support
Enhanced audit logging - Tamper-evident, comprehensive event tracking
REST API server mode - Production-ready FastAPI server with WebSocket support
Docker containerization - Containerized deployment with Docker Compose support

Completed Features (v3.1.0+)

OpenVINO ML Integration - Neural network-based voice modification with hardware acceleration

Planned Features

Formal audit and certification support
Additional language support
Kubernetes deployment manifests
Advanced monitoring and metrics dashboard
Pre-trained voice conversion models

⚠️ Compliance Disclaimer

IMPORTANT: This system is designed to be COMPLIANT with federal voice anonymization mandates and standards. However:

Compliance ≠ Certification: Meeting specifications does not constitute formal certification
Not Audited: This system has NOT been formally audited by any authorized federal agency
Not Certified: This system has NOT been certified by NIST, NSA, or any certification body
Agency Approval Required: Production federal deployments may require formal audit and approval per your agency's security policies
Use at Own Risk: Users are responsible for ensuring compliance with their specific agency requirements

For production federal deployments:

Consult your agency's security office
Review Federal Compliance Documentation
Consider formal audit and certification if required
Verify compliance with your specific use case

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

This implementation is designed to meet federal voice anonymization mandates and forensic analysis requirements.

Technologies Used

Librosa - Audio analysis
Praat-Parselmouth - Formant extraction
Rich - Terminal UI
NumPy & SciPy - Scientific computing

📞 Support

For compliance questions, issues, or contributions:

Review Federal Compliance Documentation
Check the documentation
Verify compliance with fvoas.verify_compliance()
Consult your agency's security office for production deployments

Built for federal-compliant voice anonymization

⚠️ Compliant but Not Audited - Review compliance documentation before production use

Name		Name	Last commit message	Last commit date
Latest commit History 26 Commits
assets		assets
audioanalysisx1		audioanalysisx1
docs		docs
electron_app		electron_app
examples		examples
samples		samples
scripts		scripts
tests		tests
.dockerignore		.dockerignore
.gitignore		.gitignore
API_FEATURES.md		API_FEATURES.md
AVX2_QUICKSTART.md		AVX2_QUICKSTART.md
Dockerfile		Dockerfile
LICENSE		LICENSE
README.md		README.md
VOICE_MOD_FEATURES.md		VOICE_MOD_FEATURES.md
build_avx2.py		build_avx2.py
docker-compose.yml		docker-compose.yml
requirements-build.txt		requirements-build.txt
requirements.txt		requirements.txt
run_api_server.py		run_api_server.py
run_fvoas_electron.py		run_fvoas_electron.py
run_fvoas_interface.py		run_fvoas_interface.py
run_fvoas_tui.py		run_fvoas_tui.py
run_fvoas_web.py		run_fvoas_web.py
run_gui.py		run_gui.py
run_voice_modifier.py		run_voice_modifier.py
run_voice_modifier_gui.py		run_voice_modifier_gui.py
setup.py		setup.py

License

SWORDIntel/AUDIOANALYSISX1

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Federal Voice Anonymization and Analysis System

🎯 Overview

🔒 Primary Function: Federal-Compliant Voice Anonymization

🔐 FVOAS: Federal Voice Obfuscation and Analysis Suite

🖥️ FVOAS TUI (Terminal User Interface)

📋 Federal Compliance Verification

🔍 Secondary Function: Forensic Voice Analysis

✨ Features

🔒 Federal-Compliant Voice Anonymization (PRIMARY)

🎨 Available Anonymization Presets

Primary Anonymization Profiles (Federal-Compliant)

Dynamic Anonymization (FVOAS - Exceeds Requirements)

Other Presets (Available but Not Primary Focus)

🔍 Forensic Voice Analysis (SECONDARY)

📋 Federal Compliance Details

Mandated Requirements Met

Standards Compliance

Enhanced Audit Logging

🚀 Quick Start

Federal-Compliant Voice Anonymization

Option 1: FVOAS TUI (Recommended for Federal Systems)

Option 2: Web GUI

Option 3: REST API Server Mode

Option 4: Docker Containerization

Option 5: Python API

Forensic Voice Analysis (Secondary Function)

Option 1: Web GUI

Option 2: Command Line

Option 3: Python API

📖 Documentation

Core Documentation

🔒 Authorized Applications

Voice Anonymization - Primary Use Cases

Forensic Analysis - Secondary Use Cases

❌ Prohibited Uses

📊 Technical Specifications

Voice Anonymization

Deployment Options

Effect Parameters

🧪 Compliance Testing

Verify Compliance

Run Test Suite

🗺️ Roadmap

Current Version: 3.0.0

Completed Features (v3.0.0+)

Completed Features (v3.1.0+)

Planned Features

⚠️ Compliance Disclaimer

📄 License

🙏 Acknowledgments

Technologies Used

📞 Support

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