Ecological Sound Events Classification Based on Time-Frequency Features

被引:0
|
作者
Ming, Li [1 ]
机构
[1] Fujian Presch Educ Coll, Fuzhou, Peoples R China
关键词
environmental sound events; time-frequency features; sum and difference histograms(SDH); matching pursuit(MP);
D O I
10.1109/ISCID.2016.85
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In order to improve the accuracy of environmental sound events recognition under non-stationary noise, a sound events recognition method based on time-frequency analysis was proposed. In this method, power spectrum of the signal was firstly output in the form of time-frequency diagram. Then, sum and difference histograms(SDH) was adopted to calculate texture features. Afterwards, the matching pursuit(MP) algorithm was employed to obtain effective time-frequency features to supplement the texture features to yield higher recognition accuracy. Two experiments were conducted to demonstrate the effectiveness of these joint features for unstructured environmental sound events classification. The results show that the method can produce good performance, and is robust to noise.
引用
下载
收藏
页码:345 / 348
页数:4
相关论文
共 50 条
  • [41] A lightweight framework for unsupervised anomalous sound detection based on selective learning of time-frequency domain features
    Wang, Yawei
    Zhang, Qiaoling
    Zhang, Weiwei
    Zhang, Yi
    Applied Acoustics, 2025, 228
  • [42] An enhanced algorithm for knee joint sound classification using feature extraction based on time-frequency analysis
    Kim, Keo Sik
    Seo, Jeong Hwan
    Kang, Jin U.
    Song, Chul Gyu
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2009, 94 (02) : 198 - 206
  • [43] Heart sound classification algorithm based on time-frequency combination feature and adaptive fuzzy neural network
    Wang Q.
    Yang H.
    Pan J.
    Tian Y.
    Guo T.
    Wang W.
    Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering, 2023, 40 (06): : 1152 - 1159
  • [44] Robust Sound Classification for Surveillance using Time Frequency Audio Features
    Ul Hassan, Saleet
    Khan, Muhammad Zeeshan
    Khan, Muhammad Usman Ghani
    Saleem, Summra
    2019 INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGIES (COMTECH), 2019, : 13 - 18
  • [45] Research on bark-frequency spectral coefficients heart sound classification algorithm based on multiple window time-frequency reassignment
    Xia J.
    Sun J.
    Yang H.
    Pan J.
    Guo T.
    Wang W.
    Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering, 2024, 41 (01): : 51 - 59
  • [46] Classification of High Frequency Oscillations in intracranial EEG signals based on coupled time-frequency and image-related features
    Krikid, Fatma
    Karfoul, Ahmad
    Chaibi, Sahbi
    Kachenoura, Amar
    Nica, Anca
    Kachouri, Abdennaceur
    Jeannes, Regine Le Bouquin
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2022, 73
  • [47] A new method for power quality mixed disturbance classification based on time-frequency domain multiple features
    Zhang, Yang
    Liu, Zhigang
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2012, 32 (34): : 83 - 90
  • [48] Patient illness classification using time-frequency features derived from the photoplethysmogram
    Watson, JN
    Addison, PS
    Leonard, P
    Beattie, TF
    PROCEEDINGS OF THE 25TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: A NEW BEGINNING FOR HUMAN HEALTH, 2003, 25 : 2978 - 2981
  • [49] Robust Sound Event Classification with Local Time-Frequency Information and Convolutional Neural Networks
    Yao, Yanli
    Yu, Qiang
    Wang, Longbiao
    Dang, Jianwu
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2019: TEXT AND TIME SERIES, PT IV, 2019, 11730 : 351 - 361
  • [50] Time-Frequency Features Combination to Improve Single-Trial EEG Classification
    Yonas, A.
    Prihatmanto, A. S.
    Mengko, T. L.
    WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING, VOL 25, PT 4: IMAGE PROCESSING, BIOSIGNAL PROCESSING, MODELLING AND SIMULATION, BIOMECHANICS, 2010, 25 : 805 - 808