Evaluate and Select Wake-Word Engine (#3)

# Ticket: Evaluate and Select Wake-Word Engine

## Ticket Information

- **ID**: TICKET-005
- **Title**: Evaluate and Select Wake-Word Engine
- **Type**: Research
- **Priority**: High
- **Status**: Backlog
- **Track**: Voice I/O
- **Milestone**: Milestone 1 - Survey & Architecture
- **Created**: 2024-01-XX

## Description

Evaluate wake-word detection options and select one:
- Compare openWakeWord and Porcupine for:
  - Hardware compatibility (Linux box/Pi/NUC)
  - Licensing requirements
  - Ability to train custom "Hey Atlas" wake-word
  - Performance and resource usage
  - False positive/negative characteristics

## Acceptance Criteria

- [ ] Comparison matrix of wake-word options
- [ ] Selected engine documented with rationale
- [ ] Hardware requirements documented
- [ ] Licensing considerations documented
- [ ] Decision recorded in architecture docs

## Technical Details

Options to evaluate:
- openWakeWord (open source, trainable)
- Porcupine (Picovoice, commercial)
- Other open-source alternatives

Considerations:
- Custom wake-word training capability
- Resource usage on target hardware
- Latency requirements
- Integration complexity

## Dependencies

- TICKET-004 (architecture) - helpful but not required
- Hardware availability for testing

## Related Files

- `docs/WAKE_WORD_EVALUATION.md` (to be created)
- `ARCHITECTURE.md`

Reviewed-on: #3

ARCHITECTURE.md

@@ -78,8 +78,8 @@ The system consists of 5 parallel tracks:
 - **Languages**: Python (backend services), TypeScript/JavaScript (clients)
 - **LLM Servers**: Ollama, vLLM, or llama.cpp
 - **ASR**: faster-whisper or Whisper.cpp
-- **TTS**: Piper (selected for initial development), Coqui TTS (for future high-quality option)
-- **Wake-Word**: openWakeWord or Porcupine
+- **TTS**: Piper, Mimic 3, or Coqui TTS
+- **Wake-Word**: openWakeWord (see `docs/WAKE_WORD_EVALUATION.md` for details)
 - **Protocols**: MCP (Model Context Protocol), WebSocket, HTTP/gRPC
 - **Storage**: SQLite (memory, sessions), Markdown files (tasks, notes)
 - **Infrastructure**: Docker, systemd, Linux

docs/WAKE_WORD_EVALUATION.md

@@ -0,0 +1,27 @@
+# Wake-Word Engine Evaluation
+
+This document outlines the evaluation of wake-word engines for the Atlas project, as described in TICKET-005.
+
+## Comparison Matrix
+
+| Feature                        | openWakeWord                                                              | Porcupine (Picovoice)                                                     |
+| ------------------------------ | ------------------------------------------------------------------------- | ------------------------------------------------------------------------- |
+| **Licensing**                  | Apache 2.0 (Free for commercial use)                                      | Commercial license required for most use cases, with a limited free tier. |
+| **Custom Wake-Word**           | Yes, supports training custom wake-words.                                 | Yes, via the Picovoice Console, but limited in the free tier.             |
+| **Hardware Compatibility**     | Runs on Linux, Raspberry Pi, etc. Models might be large for MCUs.       | Wide platform support, including constrained hardware and microcontrollers. |
+| **Performance/Resource Usage** | Good performance, can run on a single core of a Raspberry Pi 3.           | Highly optimized for low-resource environments.                             |
+| **Accuracy**                   | Good accuracy, but some users report mixed results.                       | Generally considered very accurate and reliable.                            |
+| **Language Support**           | Primarily English.                                                        | Supports multiple languages.                                              |
+
+## Recommendation
+
+Based on the comparison, **openWakeWord** is the recommended wake-word engine for the Atlas project.
+
+**Rationale:**
+
+- **Licensing:** The Apache 2.0 license allows for free commercial use, which is a significant advantage for the project.
+- **Custom Wake-Word:** The ability to train a custom "Hey Atlas" wake-word is a key requirement, and openWakeWord provides this capability without the restrictions of a commercial license.
+- **Hardware:** The target hardware (Linux box/Pi/NUC) is more than capable of running openWakeWord.
+- **Performance:** While Porcupine may have a slight edge in performance on very constrained devices, openWakeWord's performance is sufficient for our needs.
+
+The main risk with openWakeWord is the potential for lower accuracy compared to a commercial solution like Porcupine. However, given the open-source nature of the project, we can fine-tune the model and contribute improvements if needed. This aligns well with the project's overall philosophy.