uncloseai-speech/docs/MODELS.md

# TTS Models and Engines

**Raccoon Mission:** Rescue abandoned open-source TTS models and integrate them into UncloseAI Speech

## Documentation Index

### Comprehensive Research
- 📊 [TTS Models Overview & Research](research/tts-models-overview.md) - Complete comparison matrix, feature analysis, and integration roadmap

### Individual Model Documentation
Each model has detailed documentation covering technical specs, integration status, and Raccoon Mission notes:

**Currently Integrated:**
- 📄 [Coqui TTS (XTTS-v2)](models/coqui-tts.md) - High-quality multilingual TTS with voice cloning
- 📄 [Piper TTS](models/piper-tts.md) - Fast, lightweight neural TTS with 100+ voices
- 📄 [Silero TTS](models/silero-tts.md) - CPU-friendly, actively maintained, 5 languages (NEW! ✨)

**High Priority Candidates:**
- 📄 [Chatterbox](models/chatterbox.md) - Emotion control, 23 languages, zero-shot cloning
- 📄 [Kokoro TTS](models/kokoro-tts.md) - Fast decoder-only architecture, Apache-2.0

**Specialized Models:**
- 📄 [Mimic 3](models/mimic3.md) - Privacy-focused, offline, lightweight
- 📄 [eSpeak NG](models/espeak-ng.md) - 100+ languages, accessibility-focused
- 📄 [Maya1](models/maya1.md) - Indic languages, diverse accents
- 📄 [Step-Audio-EditX](models/step-audio-editx.md) - LLM-based audio editing (experimental)

**Historical/Archived:**
- 📄 [Mozilla TTS](models/mozilla-tts.md) - Superseded by Coqui TTS
- 📄 [Tortoise TTS](models/tortoise-tts.md) - Studio-quality but slow (archival)

---

## Currently Integrated

### 1. Piper TTS ✅

> 📖 **See [detailed documentation](models/piper-tts.md)** for comprehensive technical specs and integration guide

**Status:** Working with absolute paths
**Original Project:** rhasspy/piper (abandoned)
**Fork:** OHF-Voice/piper1-gpl v1.3.0
**Current Package:** PyPI `piper-tts>=1.2.0`

**Features:**
- Fast CPU-based neural TTS
- ~100+ high-quality voices
- Multilingual support
- ONNX runtime
- Low memory footprint (~100MB per voice)

**Voices Available:**
- English (US, GB, multiple accents)
- Spanish, French, German, Italian
- Russian, Polish, Ukrainian
- Chinese, Japanese, Korean
- Many more languages

**Model Source:**
- HuggingFace: `rhasspy/piper-voices`
- Direct download: `https://huggingface.co/rhasspy/piper-voices/resolve/v1.0.0/`

**Integration:**
- Used for `tts-1` model (fast, lower quality)
- Models stored in `/app/voices/en/en_US/libritts_r/medium/`
- Configuration via absolute paths in `voice_to_speaker.yaml`

**Example Config:**
```yaml
tts-1:
  alloy:
    model: /app/voices/en/en_US/libritts_r/medium/en_US-libritts_r-medium.onnx
    speaker: 79
```

**Raccoon Notes:**
- Original rhasspy project abandoned
- OHF-Voice fork has no PyPI package
- Need to create our own PyPI package or vendor the code
- Mirror all voices to prevent HuggingFace dependency

---

### 2. Coqui XTTS v2 ✅

> 📖 **See [detailed documentation](models/coqui-tts.md)** for comprehensive technical specs and integration guide

**Status:** Integrated as tts-1-hd
**Original Project:** coqui-ai/TTS (company shut down, archived)
**Current Package:** PyPI `coqui-tts[languages]`

**Features:**
- High-quality multilingual TTS
- Voice cloning from 6-second samples
- Emotional prosody control
- GPU accelerated (NVIDIA/ROCm)
- ~1.8GB model size

**Languages:**
- English, Spanish, French, German, Italian, Portuguese
- Polish, Turkish, Russian, Dutch, Czech
- Arabic, Chinese (Mandarin), Japanese, Hungarian, Korean, Hindi

**Model Source:**
- HuggingFace: `coqui/XTTS-v2`
- Auto-downloaded on first use

**Integration:**
- Used for `tts-1-hd` model (slow, high quality)
- Voice cloning with custom WAV samples
- Language auto-detection with `langdetect`

**Example Config:**
```yaml
tts-1-hd:
  alloy:
    model: xtts
    speaker: /app/voices/alloy.wav
    language: en
```

**Raccoon Notes:**
- Coqui company shut down in 2024
- Repository archived but code still works
- Community forks emerging
- Must mirror XTTS-v2 weights before they disappear
- Consider forking to uncloseai-xtts

---

## High Priority Integration Targets

### 3. Silero TTS ✅

> 📖 **See [detailed documentation](models/silero-tts.md)** for comprehensive technical specs (documentation pending)

**Status:** INTEGRATED as tts-1-silero
**Project:** snakers4/silero-models (actively maintained!)
**License:** Apache 2.0

**Integration Benefits:**
- ACTIVELY MAINTAINED - no abandonment risk!
- Fast, small models (~50-100MB each)
- High quality for size
- Easy integration via PyTorch Hub
- Commercial-friendly license
- CPU friendly - no GPU required

**Features:**
- Multilingual: English, Russian, German, Spanish, French
- Multiple speakers per language (English: 117 speakers!)
- Emotion control
- Real-time capable on CPU
- 48kHz sample rate

**Models:**
- English: 117 speakers (v4_en)
- Russian: 8+ speakers (v4_ru)
- German: 1 speaker (v3_de)
- Spanish: 2 speakers (v1_es)
- French: 1 speaker (v3_fr)

**Model Source:**
- PyTorch Hub: `torch.hub.load('snakers4/silero-models')`
- Models downloaded on first use
- Cached in `/app/voices/` directory

**Integration:**
- Used for `tts-1-silero` model (fast, CPU-friendly)
- Loaded via torch.hub on demand
- 6 OpenAI-compatible voices mapped to Silero speakers

**Example Config:**
```yaml
tts-1-silero:
  alloy:
    language: en
    speaker: en_0
    silero_speaker: v4_en
```

**Makefile Targets:**
```bash
make voices-silero  # Download Silero models (en, ru, de, es, fr)
make test-silero    # Test Silero TTS endpoint
```

**Example Usage:**
```python
import torch
model, symbols, sample_rate, example_text, apply_tts = torch.hub.load(
    repo_or_dir='snakers4/silero-models',
    model='silero_tts',
    language='en',
    speaker='v4_en'
)
audio = apply_tts(text=text, speaker='en_0', sample_rate=sample_rate)
```

**Raccoon Priority:** ⭐⭐⭐⭐⭐ (Active project, great quality/size ratio)

---

### 4. StyleTTS2 🎯

**Status:** NOT INTEGRATED - HIGH PRIORITY
**Project:** yl4579/StyleTTS2 (research, somewhat active)
**License:** MIT

**Why Integrate:**
- State-of-the-art quality
- Best prosody and naturalness
- Voice cloning capability
- Style/emotion control
- Research-grade results

**Features:**
- Human-level prosody
- Zero-shot voice cloning
- Style transfer
- Emotion and speaking style control
- LibriTTS trained models

**Challenges:**
- Complex dependencies
- Requires phonemizer
- Slower than other engines
- GPU recommended

**Model Source:**
- HuggingFace: `yl4579/StyleTTS2-LibriTTS`
- GitHub releases

**Estimated Integration Effort:** 6-8 hours
- Complex dependency chain
- Need phonemizer setup
- Create custom engine wrapper
- May need model quantization for production

**Raccoon Priority:** ⭐⭐⭐⭐ (Best quality, but complex)

---

### 5. Fish Speech 🎯

**Status:** NOT INTEGRATED - MEDIUM PRIORITY
**Project:** fishaudio/fish-speech (active)
**License:** Apache 2.0

**Why Integrate:**
- Fast and efficient
- Good multilingual support
- Active development
- Clean API

**Features:**
- Fast inference
- Multilingual (EN, ZH, JA)
- Voice cloning
- Streaming support
- Modern architecture

**Model Source:**
- HuggingFace: `fishaudio/fish-speech-1`
- GitHub releases

**Estimated Integration Effort:** 4-6 hours

**Raccoon Priority:** ⭐⭐⭐ (Active, good quality, but newer/less proven)

---

## Medium Priority Targets

### 6. Kokoro TTS

> 📖 **See [detailed documentation](models/kokoro-tts.md)** for comprehensive technical specs

**Status:** NOT INTEGRATED
**Project:** hexgrad/kokoro (new, active)
**License:** Apache 2.0

**Features:**
- Fast, small, quality
- Multiple voices
- Good English support
- Emerging project

**Raccoon Priority:** ⭐⭐⭐ (Promising but new)

---

### 7. Bark (Suno AI)

**Status:** NOT INTEGRATED
**Project:** suno-ai/bark (archived, company pivoted to music)
**License:** MIT

**Why Consider:**
- Can generate music and sound effects
- Non-verbal sounds (laughs, sighs)
- Multiple languages
- Background audio

**Why Low Priority:**
- Very slow generation
- Large models (~10GB)
- Company abandoned it
- Quality inconsistent

**Raccoon Priority:** ⭐⭐ (Unique features, but slow and abandoned)

---

## Low Priority / Archived

### 8. Tortoise TTS

> 📖 **See [detailed documentation](models/tortoise-tts.md)** for comprehensive technical specs

**Status:** NOT INTEGRATED
**Project:** neonbjb/tortoise-tts (low activity)
**License:** Apache 2.0

**Features:**
- Very high quality
- Voice cloning

**Why Low Priority:**
- Extremely slow (minutes per sentence)
- Not practical for API use
- Better alternatives exist now

**Raccoon Priority:** ⭐ (Too slow for production)

---

### 9. MetaVoice

**Status:** NOT INTEGRATED
**Project:** metavoiceio/metavoice-src (partially abandoned)
**License:** Apache 2.0

**Features:**
- Long-form TTS
- Emotional control
- Voice cloning

**Why Low Priority:**
- Unclear maintenance status
- Complex setup
- Alternatives are better

**Raccoon Priority:** ⭐ (Uncertain future)

---

### 10. Mozilla TTS

> 📖 **See [detailed documentation](models/mozilla-tts.md)** for historical context and relationship to Coqui

**Status:** NOT INTEGRATED
**Project:** mozilla/TTS (archived, became Coqui)
**License:** MPL 2.0

**Why Skip:**
- Fully superseded by Coqui
- No unique capabilities
- Outdated architecture

**Raccoon Priority:** ⛔ (Skip - use Coqui instead)

---

## Integration Roadmap

### Phase 1: Quick Wins (Next 1-2 weeks)
1. ✅ Fix Piper absolute paths
2. ✅ Audit repository
3. ✅ Integrate Silero TTS (COMPLETED!)
4. [ ] Set up model mirror on ai.foxhop.net
5. [ ] Integrate Chatterbox (emotion control)
6. [ ] Integrate Kokoro (fast decoder)

### Phase 2: High Quality (2-4 weeks)
1. [ ] Integrate StyleTTS2
2. [ ] Create engine abstraction layer
3. [ ] Refactor speech.py to use engines
4. [ ] Add Fish Speech support

### Phase 3: Resilience (1-2 months)
1. [ ] Implement binary mirror system
2. [ ] Create fallback download logic
3. [ ] Archive critical models to Archive.org
4. [ ] Document all model sources

### Phase 4: Advanced Features (2+ months)
1. [ ] Voice cloning API endpoint
2. [ ] Emotion/style control
3. [ ] Streaming TTS
4. [ ] Multi-speaker conversations

## Model Storage Requirements

Current:
- Piper voices: ~2GB (all languages)
- XTTS v2: ~1.8GB

With all planned engines:
- Silero models: ~500MB (all languages)
- StyleTTS2: ~2GB (base model)
- Fish Speech: ~1.5GB
- **Total: ~8GB** for complete coverage

Mirror storage needed: ~20GB (with redundancy and archives)

## Performance Targets

| Engine | Speed (RTF) | Quality | Use Case |
|--------|-------------|---------|----------|
| Piper | 0.05x | Good | Fast API responses |
| Silero | 0.1x | Good | Balanced speed/quality |
| XTTS | 0.3x | Excellent | Voice cloning |
| StyleTTS2 | 0.5x | Best | Premium quality |
| Fish Speech | 0.15x | Very Good | Multilingual |

RTF = Real-time factor (lower is faster, 1.0 = real-time)

---

## Additional Models Under Research

The following models have detailed documentation but are not yet integrated or prioritized:

### Chatterbox
**Priority:** High - Emotion control features
📄 [Full Documentation](models/chatterbox.md)
- Multilingual zero-shot TTS from Resemble AI
- 23 languages with emotion exaggeration control
- Production-grade, actively maintained
- License: Apache-2.0

### Mimic 3
**Priority:** Medium - Privacy/embedded use cases
📄 [Full Documentation](models/mimic3.md)
- Lightweight offline TTS from Mycroft AI
- 20-50MB models, SSML support
- Privacy-focused, embeddable
- License: Apache-2.0

### eSpeak NG
**Priority:** Low - Niche accessibility use
📄 [Full Documentation](models/espeak-ng.md)
- Formant-based synthesis for 100+ languages
- Extremely portable (<10MB)
- Actively maintained by accessibility community
- License: GPL-3.0

### Step-Audio-EditX
**Priority:** Research - Experimental
📄 [Full Documentation](models/step-audio-editx.md)
- New LLM-based audio editing (November 2025)
- Post-generation emotion/style editing
- Cutting-edge but experimental
- License: Apache-2.0

### Maya1
**Priority:** Research - Emerging
📄 [Full Documentation](models/maya1.md)
- India-based multilingual voice model
- Strong Indic language support (Hindi, Tamil, etc.)
- High benchmark rankings
- License: MIT

---

**Last Updated:** 2025-11-09
**Raccoon Status:** 🦝 3 models rescued! Silero TTS integrated successfully
**Integration Status:** ✅ Piper, XTTS, Silero | 🎯 Next: Chatterbox, Kokoro
**Documentation Status:** 📚 10 models fully documented, 1 comprehensive research overview