Resumen
This paper presents the design of a voice acqui-sition and recognition system in VHDL, mainly optimized for FPGA DE1-SoC. The system implements advanced digital signal processing techniques combined with classification through the K-Nearest Neighbors (KNN) algorithm. The system operates at a 320 kHz sampling rate, with a latency of 10 ns and power consumption of 1.2 W. The design enhances precision and noise rejection through the use of Hamming windows and integer-based processing. Future improvements will focus on the implementation of neural networks to replace the KNN algorithm and further increase system accuracy.
| Idioma original | Inglés estadounidense |
|---|---|
| Título de la publicación alojada | Proceedings of the 2024 IEEE 31st International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2024 |
| Editorial | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (versión digital) | 9798350378344 |
| DOI | |
| Estado | Indizado - 2024 |
| Publicado de forma externa | Sí |
| Evento | 31st IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2024 - Lima, Perú Duración: 6 nov. 2024 → 8 nov. 2024 |
Serie de la publicación
| Nombre | Proceedings of the 2024 IEEE 31st International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2024 |
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Conferencia
| Conferencia | 31st IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2024 |
|---|---|
| País/Territorio | Perú |
| Ciudad | Lima |
| Período | 6/11/24 → 8/11/24 |
Nota bibliográfica
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