Embedded Implementation of Real-Time Voice Command Recognition on PIC Microcontroller
Gespeichert in:
| Veröffentlicht in: | Automation vol. 6, no. 4 (2025), p. 79-101 |
|---|---|
| 1. Verfasser: | |
| Weitere Verfasser: | , , |
| Veröffentlicht: |
MDPI AG
|
| Schlagworte: | |
| Online-Zugang: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| Tags: |
Keine Tags, Fügen Sie das erste Tag hinzu!
|
| Abstract: | This paper describes a real-time system for recognizing voice commands for resource-constrained embedded devices, specifically a PIC microcontroller. While most existing speech ordering support solutions rely on high-performance processing platforms or cloud computation, the system described here performs fully embedded low-power processing locally on the device. Sound is captured through a low-cost MEMS microphone, segmented into short audio frames, and time domain features are extracted (i.e., Zero-Crossing Rate (ZCR) and Short-Time Energy (STE)). These features were chosen for low power and computational efficiency and the ability to be processed in real time on a microcontroller. For the purposes of this experimental system, a small vocabulary of four command words (i.e., “ON”, “OFF”, “LEFT”, and “RIGHT”) were used to simulate real sound-ordering interfaces. The main contribution is demonstrated in the clever combination of low-complex, lightweight signal-processing techniques with embedded neural network inference, completing a classification cycle in real time (under 50 ms). It was demonstrated that the classification accuracy was over 90% using confusion matrices and timing analysis of the classifier’s performance across vocabularies with varying levels of complexity. This method is very applicable to IoT and portable embedded applications, offering a low-latency classification alternative to more complex and resource intensive classification architectures. |
|---|---|
| ISSN: | 2673-4052 |
| DOI: | 10.3390/automation6040079 |
| Quelle: | Engineering Database |