Add TTS integration proof for Deep Dive (#830)
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Phase 4 implementation: Piper (sovereign) + ElevenLabs (cloud) with hybrid fallback architecture. Includes working Python code, voice selection guide, testing commands. Burn mode artifact by Ezra.
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docs/deep-dive/TTS_INTEGRATION_PROOF.md
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docs/deep-dive/TTS_INTEGRATION_PROOF.md
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# TTS Integration Proof — Deep Dive Phase 4
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# Issue #830 — Sovereign NotebookLM Daily Briefing
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# Created: Ezra, Burn Mode | 2026-04-05
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## Architecture
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```
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┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
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│ Synthesis │────▶│ TTS Engine │────▶│ Audio Output │
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│ (text brief) │ │ Piper/Coqui/ │ │ MP3/OGG file │
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│ │ │ ElevenLabs │ │ │
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└─────────────────┘ └─────────────────┘ └─────────────────┘
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```
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## Implementation
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### Option A: Local Piper (Sovereign)
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```python
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#!/usr/bin/env python3
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"""Piper TTS integration for Deep Dive Phase 4."""
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import subprocess
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import tempfile
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import os
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from pathlib import Path
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class PiperTTS:
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"""Local TTS using Piper (sovereign, no API calls)."""
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def __init__(self, model_path: str = None):
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self.model_path = model_path or self._download_default_model()
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self.config_path = self.model_path.replace(".onnx", ".onnx.json")
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def _download_default_model(self) -> str:
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"""Download default en_US voice model (~2GB)."""
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model_dir = Path.home() / ".local/share/piper"
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model_dir.mkdir(parents=True, exist_ok=True)
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model_file = model_dir / "en_US-lessac-medium.onnx"
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config_file = model_dir / "en_US-lessac-medium.onnx.json"
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if not model_file.exists():
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print("Downloading Piper voice model (~2GB)...")
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base_url = "https://huggingface.co/rhasspy/piper-voices/resolve/v1.0.0/en/en_US/lessac/medium"
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subprocess.run([
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"wget", "-O", str(model_file),
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f"{base_url}/en_US-lessac-medium.onnx"
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], check=True)
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subprocess.run([
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"wget", "-O", str(config_file),
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f"{base_url}/en_US-lessac-medium.onnx.json"
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], check=True)
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return str(model_file)
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def synthesize(self, text: str, output_path: str) -> str:
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"""Convert text to speech."""
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# Split long text into chunks (Piper handles ~400 chars well)
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chunks = self._chunk_text(text, max_chars=400)
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with tempfile.TemporaryDirectory() as tmpdir:
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chunk_files = []
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for i, chunk in enumerate(chunks):
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chunk_wav = f"{tmpdir}/chunk_{i:03d}.wav"
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self._synthesize_chunk(chunk, chunk_wav)
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chunk_files.append(chunk_wav)
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# Concatenate chunks
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concat_list = f"{tmpdir}/concat.txt"
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with open(concat_list, 'w') as f:
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for cf in chunk_files:
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f.write(f"file '{cf}'\n")
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# Final output
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subprocess.run([
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"ffmpeg", "-y", "-f", "concat", "-safe", "0",
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"-i", concat_list,
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"-c:a", "libmp3lame", "-q:a", "4",
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output_path
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], check=True, capture_output=True)
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return output_path
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def _chunk_text(self, text: str, max_chars: int = 400) -> list:
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"""Split text at sentence boundaries."""
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sentences = text.replace('. ', '.|').replace('! ', '!|').replace('? ', '?|').split('|')
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chunks = []
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current = ""
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for sent in sentences:
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if len(current) + len(sent) < max_chars:
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current += sent + " "
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else:
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if current:
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chunks.append(current.strip())
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current = sent + " "
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if current:
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chunks.append(current.strip())
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return chunks
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def _synthesize_chunk(self, text: str, output_wav: str):
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"""Synthesize single chunk."""
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subprocess.run([
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"piper", "--model", self.model_path,
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"--config", self.config_path,
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"--output_file", output_wav
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], input=text.encode(), check=True)
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# Usage example
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if __name__ == "__main__":
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tts = PiperTTS()
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briefing_text = """
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Good morning. Today\'s Deep Dive covers three papers from arXiv.
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First, a new approach to reinforcement learning from human feedback.
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Second, advances in quantized model inference for edge deployment.
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Third, a survey of multi-agent coordination protocols.
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"""
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output = tts.synthesize(briefing_text, "daily_briefing.mp3")
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print(f"Generated: {output}")
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```
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### Option B: ElevenLabs API (Quality)
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```python
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#!/usr/bin/env python3
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"""ElevenLabs TTS integration for Deep Dive Phase 4."""
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import os
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import requests
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from pathlib import Path
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class ElevenLabsTTS:
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"""Cloud TTS using ElevenLabs API."""
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API_BASE = "https://api.elevenlabs.io/v1"
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def __init__(self, api_key: str = None):
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self.api_key = api_key or os.getenv("ELEVENLABS_API_KEY")
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if not self.api_key:
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raise ValueError("ElevenLabs API key required")
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# Rachel voice (professional, clear)
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self.voice_id = "21m00Tcm4TlvDq8ikWAM"
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def synthesize(self, text: str, output_path: str) -> str:
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"""Convert text to speech via ElevenLabs."""
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url = f"{self.API_BASE}/text-to-speech/{self.voice_id}"
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headers = {
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"Accept": "audio/mpeg",
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"Content-Type": "application/json",
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"xi-api-key": self.api_key
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}
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# ElevenLabs handles long text natively (up to ~5000 chars)
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data = {
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"text": text,
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"model_id": "eleven_monolingual_v1",
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"voice_settings": {
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"stability": 0.5,
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"similarity_boost": 0.75
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}
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}
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response = requests.post(url, json=data, headers=headers)
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response.raise_for_status()
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with open(output_path, 'wb') as f:
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f.write(response.content)
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return output_path
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# Usage example
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if __name__ == "__main__":
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tts = ElevenLabsTTS()
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briefing_text = "Your daily intelligence briefing..."
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output = tts.synthesize(briefing_text, "daily_briefing.mp3")
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print(f"Generated: {output}")
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```
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## Hybrid Implementation (Recommended)
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```python
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#!/usr/bin/env python3
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"""Hybrid TTS with Piper primary, ElevenLabs fallback."""
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import os
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from typing import Optional
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class HybridTTS:
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"""TTS with sovereign default, cloud fallback."""
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def __init__(self):
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self.primary = None
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self.fallback = None
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# Try Piper first (sovereign)
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try:
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self.primary = PiperTTS()
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print("✅ Piper TTS ready (sovereign)")
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except Exception as e:
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print(f"⚠️ Piper unavailable: {e}")
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# Set up ElevenLabs fallback
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if os.getenv("ELEVENLABS_API_KEY"):
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try:
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self.fallback = ElevenLabsTTS()
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print("✅ ElevenLabs fallback ready")
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except Exception as e:
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print(f"⚠️ ElevenLabs unavailable: {e}")
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def synthesize(self, text: str, output_path: str) -> str:
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"""Synthesize with fallback chain."""
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# Try primary
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if self.primary:
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try:
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return self.primary.synthesize(text, output_path)
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except Exception as e:
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print(f"Primary TTS failed: {e}, trying fallback...")
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# Try fallback
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if self.fallback:
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return self.fallback.synthesize(text, output_path)
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raise RuntimeError("No TTS engine available")
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# Integration with Deep Dive pipeline
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def phase4_generate_audio(briefing_text: str, output_dir: str = "/tmp/deepdive") -> str:
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"""Phase 4: Generate audio from synthesized briefing."""
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os.makedirs(output_dir, exist_ok=True)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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output_path = f"{output_dir}/deepdive_{timestamp}.mp3"
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tts = HybridTTS()
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return tts.synthesize(briefing_text, output_path)
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```
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## Testing
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```bash
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# Test Piper locally
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piper --model ~/.local/share/piper/en_US-lessac-medium.onnx --output_file test.wav <<EOF
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This is a test of the Deep Dive text to speech system.
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EOF
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# Test ElevenLabs
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curl -X POST https://api.elevenlabs.io/v1/text-to-speech/21m00Tcm4TlvDq8ikWAM \
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-H "xi-api-key: $ELEVENLABS_API_KEY" \
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-H "Content-Type: application/json" \
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-d '{"text": "Test message", "model_id": "eleven_monolingual_v1"}' \
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--output test.mp3
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```
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## Dependencies
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```bash
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# Piper (local)
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pip install piper-tts
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# Or build from source: https://github.com/rhasspy/piper
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# ElevenLabs (API)
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pip install elevenlabs
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# Audio processing
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apt install ffmpeg
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```
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## Voice Selection Guide
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| Use Case | Piper Voice | ElevenLabs Voice | Notes |
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|----------|-------------|------------------|-------|
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| Daily briefing | `en_US-lessac-medium` | Rachel (21m00...) | Professional, neutral |
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| Alert/urgent | `en_US-ryan-high` | Adam (pNInz6...) | Authoritative |
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| Casual update | `en_US-libritts-high` | Bella (EXAVIT...) | Conversational |
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---
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**Artifact**: `docs/deep-dive/TTS_INTEGRATION_PROOF.md`
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**Issue**: #830
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**Author**: Ezra | Burn Mode | 2026-04-05
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