Detection and Recognition of Voice Commands by a Distributed Acoustic Sensor Based on Phase-Sensitive OTDR in the Smart Home Concept

Sensors (Basel, Switzerland) Pub Date : 2024-04-01 DOI:10.3390/s24072281

Tatyana V. Gritsenko, M. V. Orlova, A. Zhirnov, Yuri A. Konstantinov, A. T. Turov, Fedor L. Barkov, Roman I. Khan, K. Koshelev, Cesare Svelto, Alexey B Pnev

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Abstract

In recent years, attention to the realization of a distributed fiber-optic microphone for the detection and recognition of the human voice has increased, whereby the most popular schemes are based on φ-OTDR. Many issues related to the selection of optimal system parameters and the recognition of registered signals, however, are still unresolved. In this research, we conducted theoretical studies of these issues based on the φ-OTDR mathematical model and verified them with experiments. We designed an algorithm for fiber sensor signal processing, applied a testing kit, and designed a method for the quantitative evaluation of our obtained results. We also proposed a new setup model for lab tests of φ-OTDR single coordinate sensors, which allows for the quick variation of their parameters. As a result, it was possible to define requirements for the best quality of speech recognition; estimation using the percentage of recognized words yielded a value of 96.3%, and estimation with Levenshtein distance provided a value of 15.

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智能家居概念中基于相位敏感 OTDR 的分布式声学传感器对语音指令的检测和识别

近年来，人们越来越关注如何实现分布式光纤麦克风对人声的检测和识别，其中最流行的方案是基于φ-OTDR。然而，与选择最佳系统参数和识别注册信号有关的许多问题仍未得到解决。在这项研究中，我们基于 φ-OTDR 数学模型对这些问题进行了理论研究，并通过实验进行了验证。我们设计了一种光纤传感器信号处理算法，应用了一套测试工具，并设计了一种对所获结果进行定量评估的方法。我们还为 φ-OTDR 单坐标传感器的实验室测试提出了一种新的设置模型，可以快速改变其参数。因此，我们可以确定最佳语音识别质量的要求；使用识别单词百分比进行估算的结果为 96.3%，而使用莱文斯坦距离进行估算的结果为 15%。

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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Sensors (Basel, Switzerland)

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