Recognition and location of marine animal sounds using two-stream ConvNet with attention - Hu, Shaoxiang; Hou, Rong; Liao, Zhiwu; Chen, Peng (Frontiers in Marine Science, 2023)
There are abundant resources and many endangered marine animals in the ocean. Using sound to effectively identify and locate them, and estimate their distribution area, has a very important role in the study of the complex diversity of marine animals[1]. We design a Two-Stream ConvNet with Attention (TSCA) model, which is a two-stream model combined with attention, in which one branch processes the temporal signal and the other branch processes the frequency domain signal; It makes good use of the characteristics of high time resolution of time domain signal and high recognition rate of frequency domain signal features of sound, and it realizes rapid localization and recognition of sound of marine species. The basic network architecture of the model is YOLO(You Only Look Once) [2]. A new loss function focal loss is constructed to strengthen the impact on the tail class of the sample, overcome the problem of data imbalance and avoid over fitting. At the same time, the attention module is constructed to focus on more detailed sound features, so as to improve the noise resistance of the model and achieve high-precision marine species identification and location. The experimental results show that the algorithm has good robustness, high recognition accuracy and positioning accuracy.