Animal Sound Classification Using A Convolutional Neural Network

被引：0
|
作者：
Sasmaz, Emre [1 ]
Tek, F. Boray [1 ]
机构：
[1] Isik Univ, Dept Comp Engn, Istanbul, Turkey
来源：
2018 3RD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ENGINEERING (UBMK) | 2018年
关键词：
Animal sound classification; Mel Frequency Cepstral Coefficient (MFCC); Convolution Neural Network (CNN); Confusion Matrix (CF);
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we investigate the problem of animal sound classification using deep learning and propose a system based on convolutional neural network architecture. As the input to the network, sound files were preprocessed to extract Mel Frequency Cepstral Coefficients (MFCC) using LibROSA library. To train and test the system we have collected 875 animal sound samples from an online sound source site for 10 different animal types. We report classification confusion matrices and the results obtained by different gradient descent optimizers. The best accuracy of 75% was obtained by Nesterov-accelerated Adaptive Moment Estimation (Nadam).
引用
收藏
页码：625 / 629
页数：5
相关论文
共 50 条
  • [21] Attention based convolutional recurrent neural network for environmental sound classification
    Zhang, Zhichao
    Xu, Shugong
    Zhang, Shunqing
    Qiao, Tianhao
    Cao, Shan
    NEUROCOMPUTING, 2021, 453 (453) : 896 - 903
  • [22] Deep Convolutional Neural Network with Transfer Learning for Environmental Sound Classification
    Lu, Jianrui
    Ma, Ruofei
    Liu, Gongliang
    Qin, Zhiliang
    2021 INTERNATIONAL CONFERENCE ON COMPUTER, CONTROL AND ROBOTICS (ICCCR 2021), 2021, : 242 - 245
  • [23] Parralel Recurrent Convolutional Neural Network for Abnormal Heart Sound Classification
    Gharehbaghi, Arash
    Partovi, Elaheh
    Babic, Ankica
    CARING IS SHARING-EXPLOITING THE VALUE IN DATA FOR HEALTH AND INNOVATION-PROCEEDINGS OF MIE 2023, 2023, 302 : 526 - 530
  • [24] Deep convolutional neural network for environmental sound classification via dilation
    Roy, Sanjiban Sekhar
    Mihalache, Sanda Florentina
    Pricop, Emil
    Rodrigues, Nishant
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2022, 43 (02) : 1827 - 1833
  • [25] Environmental sound classification using temporal-frequency attention based convolutional neural network
    Wenjie Mu
    Bo Yin
    Xianqing Huang
    Jiali Xu
    Zehua Du
    Scientific Reports, 11
  • [26] Environmental sound classification using temporal-frequency attention based convolutional neural network
    Mu, Wenjie
    Yin, Bo
    Huang, Xianqing
    Xu, Jiali
    Du, Zehua
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [27] Classification of stroke disease using convolutional neural network
    Marbun, J. T.
    Seniman
    Andayani, U.
    2ND INTERNATIONAL CONFERENCE ON COMPUTING AND APPLIED INFORMATICS 2017, 2018, 978
  • [28] The Classification of Hypertensive Retinopathy using Convolutional Neural Network
    Triwijoyo, Bambang Krismono
    Budiharto, Widodo
    Abdurachman, Edi
    DISCOVERY AND INNOVATION OF COMPUTER SCIENCE TECHNOLOGY IN ARTIFICIAL INTELLIGENCE ERA, 2017, 116 : 166 - 173
  • [29] Automatic Document Classification Using Convolutional Neural Network
    Sun, Xingping
    Li, Yibing
    Kang, Hongwei
    Shen, Yong
    2018 INTERNATIONAL SEMINAR ON COMPUTER SCIENCE AND ENGINEERING TECHNOLOGY (SCSET 2018), 2019, 1176
  • [30] Wetland Classification Using Deep Convolutional Neural Network
    Mandianpari, Masoud
    Rezaee, Mohammad
    Zhang, Yun
    Salehi, Bahram
    IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 9249 - 9252
12345