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嵌入式系统中的声音方向检测与混合声源分离的实现。

Implementation of Sound Direction Detection and Mixed Source Separation in Embedded Systems.

机构信息

School of Computer Science and Technology, Shandong University of Technology, Zibo 255000, China.

Department of Computer Science and Information Engineering, Fu Jen Catholic University, New Taipei City 242062, Taiwan.

出版信息

Sensors (Basel). 2024 Jul 4;24(13):4351. doi: 10.3390/s24134351.

Abstract

In recent years, embedded system technologies and products for sensor networks and wearable devices used for monitoring people's activities and health have become the focus of the global IT industry. In order to enhance the speech recognition capabilities of wearable devices, this article discusses the implementation of audio positioning and enhancement in embedded systems using embedded algorithms for direction detection and mixed source separation. The two algorithms are implemented using different embedded systems: direction detection developed using TI TMS320C6713 DSK and mixed source separation developed using Raspberry Pi 2. For mixed source separation, in the first experiment, the average signal-to-interference ratio (SIR) at 1 m and 2 m distances was 16.72 and 15.76, respectively. In the second experiment, when evaluated using speech recognition, the algorithm improved speech recognition accuracy to 95%.

摘要

近年来,用于监测人们活动和健康的传感器网络和可穿戴设备的嵌入式系统技术和产品已成为全球 IT 行业的焦点。为了提高可穿戴设备的语音识别能力,本文讨论了使用嵌入式算法进行方向检测和混合源分离,在嵌入式系统中实现音频定位和增强。这两个算法使用不同的嵌入式系统实现:使用 TI TMS320C6713 DSK 开发的方向检测和使用 Raspberry Pi 2 开发的混合源分离。对于混合源分离,在第一个实验中,在 1 米和 2 米的距离处的平均信干比(SIR)分别为 16.72 和 15.76。在第二个实验中,使用语音识别进行评估时,该算法将语音识别的准确率提高到 95%。

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