RISC-V based sound classifier intended for acoustic surveillance in protected natural environments

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Resumen

This paper presents results on FPGA of a RISC-V based Application Specific Processor (ASP), used as the main classification unit for acoustic pattern recognition of firearms and chainsaws in environmentally protected areas. The classifier is based on the Hidden Markov Models (HMM) technique, giving a probabilistic estimation of the current state of an acoustic environment, thereby identifying particular sounds such as gunshots or the hum from a chainsaw engine. The ASP was modeled in Verilog, and uses Berkeley's RISC-V's open Instruction Set Architecture (ISA). The code is written in C and ported to the ASP using RISC-V's toolchain. Verified results on a commercial FPGA, and preliminary synthesis results in a commercial CMOS 130nm process, point at the feasibility of a low power ASIC implementation, integrated into a wireless network of similar nodes.

Idioma originalInglés
Título de la publicación alojadaLASCAS 2017 - 8th IEEE Latin American Symposium on Circuits and Systems, R9 IEEE CASS Flagship Conference
Subtítulo de la publicación alojadaProceedings
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781509058594
DOI
EstadoPublicada - 13 jun 2017
Evento8th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2017 - Bariloche, Argentina
Duración: 20 feb 201723 feb 2017

Serie de la publicación

NombreLASCAS 2017 - 8th IEEE Latin American Symposium on Circuits and Systems, R9 IEEE CASS Flagship Conference: Proceedings

Conferencia

Conferencia8th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2017
País/TerritorioArgentina
CiudadBariloche
Período20/02/1723/02/17

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