Acoustic bird species classification under low SNR and small-scale dataset conditions

•A CFAR-based adaptive threshold scheme is proposed to more effectively select potential bird vocalization segments.•Fusion of LWAP and MFCC features after improved VLAD encoding is employed and corresponding feature space analysis is presented.•Our method outperforms other feature extraction based and deep learning based methods for low SNR and small-scale datasets.