Eco-environmental Sounds Classification with Time-frequency Features under Noise Conditions
YU Qingqing
Abstract：Eco-environmental sounds depict the sound content of varieties of creatures' survival and activities in the ecological environment at a time interval.Research on eco-environmental sounds is useful in monitoring of the wildlife and their evolution with time.Due to varieties of noises in the ecological environment,the task of eco-environmental sounds classification under noise conditions is considered.Time-frequency representations have the potential to be powerful features for nonstationary signals.Especially,time-frequency domain features can classify sounds with noise where using frequency-domain features (e.g.,MFCCs) fail.Hence,a classification approach using time-frequency features for eco-environmental sounds under noise conditions is presented in this paper.Matching pursuit (MP) algorithm is proposed to extract time-frequency features (MP-based features,for short) of effective signals.Besides statistical features extracted under Choi-Williams distribution (CWD-based features,for short) also perform more effectively than other conventional audio features under noise conditions.Considering the effectiveness of features and robustness of classifier,a classification model using time-frequency features (the combination features of MP based features and CWD-based features) and support vector machine (MP+CWD-SVM for short) is proposed.Experimentally,CWD+MP-SVM is able to achieve a higher classification rate for eco-environmental sounds under noise conditions.The result shows that time-frequency features and SVM classifier have better noise immunity.
Keywords：time-frequency featuresmatching pursuitChoi-Williams distributioneco-environmental sounds
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 8-14,106 )