2.6 KiB
2.6 KiB
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.