How to Choose a Voice-Control Solution
Choose the architecture from the product requirements first: vocabulary, connectivity, device resources, privacy, latency and manufacturing model.
Common paths
| Path | Good fit | Main trade-off |
|---|---|---|
| Lightweight KWS | Two to dozens of fixed words, offline control | Cannot understand arbitrary sentences |
| Offline ASR | Open speech, names and numbers | Larger models and higher resource use |
| Cloud ASR | Fast access to open recognition | Network, latency, privacy and recurring cost |
| Voice module or closed SDK | Ready-made hardware or vendor stack | Format, license and supplier lock-in |
Five questions before choosing
- Are the phrases fixed or open-ended?
- Must the product work without a network?
- What are the memory, power and latency budgets?
- Which ONNX/TFLite-compatible target platforms must be supported?
- Is this a prototype or a product that will be maintained for years?
When KWS is the better first step
If the product needs “start”, “stop”, “open”, “close” or “next”, KWS is usually smaller, faster and easier to validate offline. A multi-keyword model can cover several actions without running a separate model for every phrase.
When ASR is necessary
Use ASR when users can say many different sentences, such as requests containing names, numbers or arbitrary parameters. KWS is not a replacement for open speech recognition.
Whatever path you choose, test recall, false triggers, latency, power and cost on the final microphone and device.
Test fixed keywords online →View the open-source inference engine and demo models →
ONNX / TFLite · Android · ESP32 · Web · Python · Home Assistant