Added detailed documentation for 10 TTS models: - Coqui TTS (XTTS-v2): High-quality multilingual with voice cloning - Mozilla TTS: Historical context, superseded by Coqui - Piper TTS: Fast, lightweight, 100+ voices - Chatterbox: Emotion control, 23 languages - Mimic 3: Privacy-focused, offline capable - eSpeak NG: 100+ languages, accessibility-focused - Kokoro TTS: Fast decoder-only architecture - Tortoise TTS: Studio-quality but slow - Step-Audio-EditX: Experimental LLM-based audio editing - Maya1: Indic languages specialist Created comprehensive research overview: - Complete model comparison matrix - Performance characteristics and feature analysis - License compatibility analysis - Integration roadmap and priorities - Raccoon Mission risk assessment Updated MODELS.md: - Added documentation index with links to all model docs - Added research overview reference - Added detailed doc references in existing sections - Added "Additional Models Under Research" section All documentation follows Raccoon Mission theme of rescuing abandoned open-source TTS models for long-term preservation.
205 lines
8.3 KiB
Markdown
205 lines
8.3 KiB
Markdown
# Mimic 3
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## Overview
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**Name:** Mimic 3
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**Description:** High-speed, offline Text-to-Speech (TTS) engine developed by Mycroft AI, specifically optimized for privacy-focused applications. Mimic 3 is designed to provide fast speech synthesis while maintaining complete data privacy by running entirely offline without requiring cloud connectivity or data transmission to external servers.
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## Key Features
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### Core Capabilities
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- **Lightweight Models**: Mimic 3 offers lightweight model packages under 100MB in size, making it suitable for resource-constrained environments and edge deployments
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- **Customizable Voices**: Multiple voice options and the ability to customize voice characteristics for different use cases
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- **SSML Support**: Full support for Speech Synthesis Markup Language (SSML) to control prosody, pitch, rate, and other speech characteristics
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### Pros
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- **Embeddable**: Designed to be easily integrated into applications without external dependencies
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- **Offline Operation**: Operates entirely offline, eliminating network latency and privacy concerns
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- **Fast Synthesis**: Optimized for speed while maintaining quality output
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- **Privacy-First**: No data leaves the device; suitable for sensitive applications
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### Cons
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- **Rule-Based Elements**: Some aspects of the engine rely on rule-based synthesis which can occasionally produce robotic-sounding output
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- **Limited Voice Variety**: Fewer voice options compared to cloud-based TTS services
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- **Limited Language Support**: Primary focus on English with limited support for other languages
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## License
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**Apache-2.0**
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The Apache License 2.0 allows for free, open-source use with minimal restrictions while providing patent protection.
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## Links
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### Official Resources
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- **GitHub**: [Mycroft AI / Mimic 3](https://github.com/MycroftAI/mimic3)
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- **Documentation**: [Mimic 3 Documentation](https://mycroft-ai.gitbook.io/mimic-3/)
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- **Project Homepage**: [Mycroft AI](https://mycroft.ai/)
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## Integration Status
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**Status:** Not integrated - Candidate for integration
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Mimic 3 is currently not integrated into this project but represents a strong candidate for future integration due to its privacy-first design, offline capabilities, and open-source nature. Integration would provide users with an embeddable, privacy-preserving TTS option.
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## Technical Details
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### Model Architecture
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Mimic 3 uses Glow-TTS (Generative Flow for Invertible 1x1 Convolutions based Generative Flow for Parallel Wavenet), a flow-based generative model for fast and parallel speech synthesis.
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### Model Sizes
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- **Lightweight Models**: 20-50 MB per voice model
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- **Total Installation**: Full installation with multiple voices typically under 500 MB
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- **Memory Usage**: Relatively low RAM requirements, suitable for embedded systems
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### SSML Support
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Mimic 3 provides comprehensive SSML support including:
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- Pitch control
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- Speech rate adjustment
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- Volume control
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- Phoneme-level pronunciation control
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- Emphasis and stress markers
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- Pause insertion
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```xml
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<speak>
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<prosody pitch="high" rate="fast">This is spoken quickly.</prosody>
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<prosody pitch="low" rate="slow">This is spoken slowly.</prosody>
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</speak>
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```
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### Offline Capabilities
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- **No Network Required**: Complete text-to-speech synthesis without internet connectivity
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- **No Cloud Dependencies**: All processing occurs on the device
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- **Deterministic Output**: Consistent results for the same input
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### Supported Formats
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- **Input**: Plain text, SSML, SSML files
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- **Output**: WAV, PCM, JSON (with phoneme information)
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## Performance
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### Speed
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- **Synthesis Speed**: Real-time synthesis; can process speech faster than real-time on modern hardware
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- **Latency**: Minimal latency for single sentences (typically under 100ms)
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- **Batch Processing**: Efficient batch processing for multiple utterances
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### Resource Usage
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- **CPU**: Moderate CPU usage; optimized for both CPU and GPU inference
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- **GPU Support**: Optional GPU acceleration available for Nvidia GPUs
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- **Memory**: Modest RAM footprint, typically 100-300 MB during operation
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- **Disk Space**: Models require minimal disk space (20-50 MB per voice)
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### Benchmark Comparisons
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| Metric | Mimic 3 | Cloud TTS (Typical) |
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|--------|---------|-------------------|
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| Latency | ~50-100ms | 500-2000ms |
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| Privacy | Local only | Cloud-dependent |
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| Cost | Free (self-hosted) | Pay per request |
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| Offline capability | Yes | No |
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## Privacy Features
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### Why Mimic 3 is Excellent for Privacy-Focused Applications
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#### Data Isolation
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- All text and synthesized speech remain on the user's device
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- No transmission to external servers or third-party services
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- Complete local processing without any data exfiltration
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#### No Telemetry
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- Open-source codebase allows verification of absence of tracking
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- No analytics or usage tracking mechanisms
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- No user profiling or behavioral analysis
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#### Compliance
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- Suitable for GDPR, HIPAA, and other privacy regulations
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- No data processing agreements with third parties needed
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- Ideal for healthcare, education, and sensitive applications
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#### Security Implications
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- Reduces attack surface compared to cloud-based services
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- Eliminates risks from data breaches at service providers
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- Control over model updates and software versions
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- Can be run in air-gapped environments
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### Use Cases
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- Healthcare applications (patient privacy protection)
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- Education software (student data protection)
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- Government and defense systems (classified content handling)
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- IoT and embedded devices (no internet required)
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- Accessibility tools (private communication aids)
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## Raccoon Mission Notes
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### Mycroft AI Status
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Mycroft AI has undergone significant changes in recent years, with the company's focus shifting and financial challenges impacting development. As of the last update, development of Mimic 3 has slowed, though the project remains open-source and functional.
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### Integration Potential
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- **High Priority**: Mimic 3 represents excellent value for privacy-conscious users
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- **Low Complexity**: Relatively straightforward integration into existing TTS frameworks
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- **Community Value**: Strong community interest in open-source, privacy-first TTS solutions
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- **Future-Proof**: Open-source ensures longevity even if primary developers step back
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### Preservation Needs
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- **Active Maintenance**: Monitor project for updates and security patches
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- **Community Forks**: Multiple community forks exist that may offer additional features or bug fixes
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- **Documentation**: Comprehensive documentation critical as official project activity may decrease
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- **Testing**: Regular testing with latest Python versions and dependencies essential
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- **Dependency Management**: Watch for deprecated dependencies that may break functionality
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### Integration Recommendations
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1. **Wrapper Development**: Create a standardized wrapper following project's TTS interface
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2. **Voice Management**: Implement voice downloading and caching mechanisms
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3. **Fallback Strategy**: Use as fallback option when cloud TTS is unavailable
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4. **Documentation**: Provide clear setup and troubleshooting guides
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5. **Community Engagement**: Monitor Mycroft AI community for updates and best practices
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## Getting Started
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### Installation
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```bash
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pip install mimic3-tts
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```
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### Basic Usage
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```python
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from mimic3_tts import Mimic3
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# Initialize Mimic 3
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engine = Mimic3(voice='en_US/cmu_arctic-male')
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# Synthesize speech
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audio_data = engine.say("Hello, this is Mimic 3 speaking!")
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# Save to file
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with open('output.wav', 'wb') as f:
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f.write(audio_data)
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```
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### Docker Usage
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```bash
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docker run -it mycroftaidev/mimic3:latest mimic3 --help
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```
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## Related Models
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- **Coqui TTS**: Another open-source offline TTS alternative with good voice quality
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- **Glow-TTS**: The underlying generative model used by Mimic 3
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- **Piper**: Another open-source TTS with better voice quality but larger models
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## References
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- Mimic 3 GitHub Repository: https://github.com/MycroftAI/mimic3
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- Mycroft AI Documentation: https://mycroft-ai.gitbook.io/mimic-3/
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- Paper: "Glow-TTS: A Generative Flow for Parallel TTS" (Movalin et al., 2020)
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## Notes
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This documentation is maintained as part of the Raccoon Mission to preserve and document open-source speech technology solutions. Mimic 3 represents an important example of privacy-first, embeddable TTS technology that deserves preservation and continued development.
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---
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*Last Updated: 2025-11-09*
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*Status: Candidate for Integration*
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