Speaker Identification with Edge AI

Identifying who is speaking from voice characteristics without recognizing what is said. Extracts speaker embeddings from short audio segments and matches against enrolled voice profiles stored on-device. Used for personalization, multi-user device access, and voice-based authentication. Privacy-preserving since raw audio never leaves the device. Requires more memory than keyword spotting due to embedding model complexity.

Hardware Requirements

Minimum RAM 128 KB
Minimum Flash 1024 KB
Sensor Inputs microphone
Typical Model Size 100 KB (quantized int8)
Minimum Clock 80 MHz

Hardware Guides

No hardware guides for speaker identification yet. Use the MCU Checker to find compatible hardware.

Industry Applications

Smart Home Security Consumer Electronics Healthcare

Build Speaker Identification with ForestHub

ForestHub compiles visual AI workflows to C code for your microcontroller. Choose your hardware, build your speaker identification pipeline, deploy in minutes.