Three-dimensional acoustic localisation via directed movements of a two-dimensional model of the lizard peripheral auditory system

Danish Shaikh, Michael Kjær Schmidt
{"title":"Three-dimensional acoustic localisation via directed movements of a two-dimensional model of the lizard peripheral auditory system","authors":"Danish Shaikh, Michael Kjær Schmidt","doi":"10.1109/IRIS.2017.8250093","DOIUrl":null,"url":null,"abstract":"Three-dimensional acoustic localisation is relevant in personal and social robot platforms. Conventional approaches extract interaural time difference cues via impractically large stationary two-dimensional multi-microphone grids with at least four microphones or spectral cues via head-related transfer functions of stationary KEMAR dummy heads equipped with two microphones. We present a preliminary approach using two sound sensors, whose directed movements resolve the location of a stationary acoustic target in three dimensions. A model of the peripheral auditory system of lizards provides sound direction information in a single plane which by itself is insufficient to localise the acoustic target in three dimensions. Two spatial orientations of this plane by rotating the sound sensors by −45° and +45° along the sagittal axis generate a pair of measurements, each encoding the location of the acoustic target with respect to one plane of rotation. A multi-layer perceptron neural network is trained via supervised learning to translate the combination of the two measurements into an estimate of the relative location of the acoustic target in terms of its azimuth and elevation. The acoustic localisation performance of the system is evaluated in simulation for noiseless as well as noisy sinusoidal auditory signals with a 20 dB signal-to-noise ratio for four different sound frequencies of 1450 Hz, 1650 Hz, 1850 Hz and 2050 Hz that span the response frequency range of the peripheral auditory model. Three different neural networks with respectively one hidden layer with ten neurons, one hidden layer with twenty neurons and two hidden layers with ten neurons are comparatively evaluated. The neural networks are evaluated for varying locations of the acoustic target on the surface of the frontal spherical section in space defined by an azimuth and elevation range of [−90°, +90°] with a resolution of 1° in both planes.","PeriodicalId":213724,"journal":{"name":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRIS.2017.8250093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Three-dimensional acoustic localisation is relevant in personal and social robot platforms. Conventional approaches extract interaural time difference cues via impractically large stationary two-dimensional multi-microphone grids with at least four microphones or spectral cues via head-related transfer functions of stationary KEMAR dummy heads equipped with two microphones. We present a preliminary approach using two sound sensors, whose directed movements resolve the location of a stationary acoustic target in three dimensions. A model of the peripheral auditory system of lizards provides sound direction information in a single plane which by itself is insufficient to localise the acoustic target in three dimensions. Two spatial orientations of this plane by rotating the sound sensors by −45° and +45° along the sagittal axis generate a pair of measurements, each encoding the location of the acoustic target with respect to one plane of rotation. A multi-layer perceptron neural network is trained via supervised learning to translate the combination of the two measurements into an estimate of the relative location of the acoustic target in terms of its azimuth and elevation. The acoustic localisation performance of the system is evaluated in simulation for noiseless as well as noisy sinusoidal auditory signals with a 20 dB signal-to-noise ratio for four different sound frequencies of 1450 Hz, 1650 Hz, 1850 Hz and 2050 Hz that span the response frequency range of the peripheral auditory model. Three different neural networks with respectively one hidden layer with ten neurons, one hidden layer with twenty neurons and two hidden layers with ten neurons are comparatively evaluated. The neural networks are evaluated for varying locations of the acoustic target on the surface of the frontal spherical section in space defined by an azimuth and elevation range of [−90°, +90°] with a resolution of 1° in both planes.
通过蜥蜴外围听觉系统的二维模型的定向运动进行三维声学定位
三维声学定位与个人和社交机器人平台相关。传统方法通过具有至少四个麦克风的大型固定二维多麦克风网格提取耳间时差线索,或者通过配备两个麦克风的固定KEMAR假头的头部相关传递函数提取频谱线索。我们提出了一种使用两个声音传感器的初步方法,它们的定向运动在三维空间中解决了静止声学目标的位置。蜥蜴的外周听觉系统模型在一个平面上提供声音方向信息,但它本身不足以在三维空间中定位声目标。通过沿矢状轴旋转声音传感器- 45°和+45°,该平面的两个空间方向产生一对测量值,每个测量值相对于一个旋转平面编码声学目标的位置。通过监督学习训练多层感知器神经网络,将两个测量值的组合转化为声目标在方位角和仰角方面的相对位置估计。系统的声学定位性能在模拟中对无噪声和有噪声的正弦听觉信号进行了评估,信噪比为20 dB,分别为1450 Hz、1650 Hz、1850 Hz和2050 Hz四种不同的声音频率,这些声音频率跨越外围听觉模型的响应频率范围。比较评价了3种不同的神经网络,分别是1层10个神经元、1层20个神经元和2层10个神经元。在方位角和仰角范围为[- 90°,+90°],两个平面分辨率均为1°的空间中,对声目标在正面球面截面表面的不同位置进行了神经网络评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信