AIoT-based Audio Recognition System for Smart Home Applications

Bo-Wei Chen, Yun-Syuan Jhang, Hao-Ting Pai, Szu-Hong Wang, M. Sheu, Tzu-Hsuing Chen
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引用次数: 2

Abstract

In this paper, we design an audio recognition system to detect events of lighters sound, which names Audio Recognition System (ARS). ARS is composed of AIOT device (i.e. Raspberry Pi), deep-learning-based analytics, and real-time alarming advisory (e.g. Line Notify). We conduct experiments with 8,000 observations. The result shows ARS achieves 97% accuracy in a quiet place and 94% accuracy in a noisy environment.
基于ai的智能家居音频识别系统
本文设计了一种检测打火机声音事件的音频识别系统,称为音频识别系统(audio recognition system, ARS)。ARS由AIOT设备(如树莓派)、基于深度学习的分析和实时报警咨询(如线路通知)组成。我们进行了8000次观察实验。结果表明,ARS在安静环境下的准确率为97%,在嘈杂环境下的准确率为94%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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