Speakers—Used as sensors for detecting acoustic loads with artificial intelligence

Author:

Kim Noori1ORCID,Kim Hui-Jun2,Kim Sung-Hee2

Affiliation:

1. School of Engineering Technology, Purdue University 1 , West Lafayette, Indiana 47907, USA

2. Department of Information Technology Convergence, Dong-eui University 2 , Busanjin-gu, Busan 47340, South Korea

Abstract

Previous research demonstrated the potential of using speakers as sensors to detect ear canal conditions. This study continues that effort by using a single speaker to measure electrical impedance across various acoustic loads. Electrical impedance data were collected and preprocessed for machine learning model training. Different image forms were tested, including magnitude only and combined magnitude phase. Using 2100 data samples with convolutional neural network-based models (AlexNet, ResNet, and DenseNet), binary and multiclass classifications achieved average accuracies of 0.9716 and 0.907, respectively. This innovative approach is set to revolutionize acoustic sensing through artificial intelligence.

Publisher

Acoustical Society of America (ASA)

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