水下无人系统学报2026，Vol.34Issue(1)：76-84,9.DOI:10.11993/j.issn.2096-3920.2025-0127
基于时频交错注意力与集成滤波模块的海洋声音分离算法
Marine Sound Separation Algorithm Based on Time-Frequency Interleaved Attention and Integrated Filtering Module
摘要
Abstract
To address the problems of refined perception and discrimination of sound features caused by complex marine soundscapes and the variable characteristics of underwater target signals,this paper proposed a marine sound separation algorithm based on time-frequency interleaved attention and an integrated filtering module(IFM).The algorithm adopted a frequency band division strategy and used an encoder to convert the mixed audio into a time-frequency spectrogram.A multi-scale attention mechanism was utilized to cross-extract time-frequency gains.The IFM efficiently fused the features extracted from the multi-scale convolutional spatial filtering and the self-attention feature dependency pathway with the original features.The fused features were input into a decoder to reconstruct high-quality pure target audio,enhancing the details of the target signals while effectively filtering out background noise and interference.Experimental results on typical marine sound datasets show that the proposed algorithm significantly improves target audio separation performance.In audio separation experiments involving humpback whales mixed with passenger ships and killer whales mixed with passenger ships,the source-to-distortion ratio improvement(SDRi)reaches 8.56 dB and 10.74 dB,respectively,and all performance indicators are superior to those of existing baseline models.关键词
海洋声景/声音分离/集成滤波模块/时频交错注意力/特征融合Key words
marine soundscape/sound separation/integrated filtration module/time-frequency interleaved attention/feature fusion分类
军事科技引用本文复制引用
王禹迪,杨明忠,刘立昕..基于时频交错注意力与集成滤波模块的海洋声音分离算法[J].水下无人系统学报,2026,34(1):76-84,9.基金项目
2024年广东省海洋经济发展项目资助(GDNRC[2024]44). （GDNRC[2024]44）
