Localization of Flying Bats from Multichannel Audio Signals by Estimating Location Map with Convolutional Neural Networks

被引：2

作者：

Fujimori, Kazuki ^{[1
]}

Raytchev, Bisser ^{[1
]}

Kaneda, Kazufumi ^{[1
]}

Yamada, Yasufumi ^{[1
]}

Teshima, Yu ^{[2
]}

Fujioka, Emyo ^{[2
]}

Hiryu, Shizuko ^{[2
]}

Tamaki, Toru ^{[3
]}

机构：

[1] Hiroshima Univ, 1-4-1 Kagamiyama, Higashihiroshima, Hiroshima 7398527, Japan

[2] Doshisha Univ, 1-3 Tatara Miyakodani, Kyotanabe, Kyoto 6100394, Japan

[3] Nagoya Inst Technol, Showa Ku, Gokiso Cho, Nagoya, Aichi 4668555, Japan

来源：

JOURNAL OF ROBOTICS AND MECHATRONICS | 2021年 / 33卷 / 03期

关键词：

bat; multichannel; ultrasound signal; CNN; location estimation; SOUND SOURCE LOCALIZATION; PIPISTRELLUS-ABRAMUS; RHINOLOPHUS-FERRUMEQUINUM; ECHOLOCATION;

D O I：

10.20965/jrm.2021.p0515

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

We propose a method that uses ultrasound audio signals from a multichannel microphone array to estimate the positions of flying bats. The proposed model uses a deep convolutional neural network that takes multichannel signals as input and outputs the probability maps of the locations of bats. We present experimental results using two ultrasound audio clips of different bat species and show numerical simulations with synthetically generated sounds.

引用

页码：515 / 525

页数：11

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