数据采集与处理2026，Vol.41Issue(2)：371-396,26.DOI:10.16337/j.1004-9037.2026.02.006
基于深度学习的声源定位与跟踪综述
Sound Source Localization and Tracking Based on Deep Learning:A Survey
摘要
Abstract
Sound source localization and tracking constitute an important means for machine hearing to acquire spatial information.With the growing adoption of multi-microphone devices in applications such as speech interaction,conference systems,and acoustic monitoring,the demand for stable estimation of a sound source's direction and position in complex acoustic environments continues to increase.Accordingly,this paper presents a systematic review of deep-learning-based techniques for sound source localization and tracking.Existing review articles have mainly focused on sound source localization,whereas deep-learning-based sound source tracking has not yet been systematically reviewed.To fill this gap,this paper presents a unified analysis of both sound source localization and tracking.First,the fundamental problem formulation and the framework of traditional approaches are outlined.Then,from the perspectives of input representation,model architecture,and learning objectives,the main lines of deep learning methods are introduced with respect to feature design,network modeling,and training strategies.Next,commonly used datasets,experimental settings,and evaluation metrics are summarized,and key considerations for comparing results under different conditions are discussed.Finally,the reviewed techniques are summarized and potential future research directions are outlined.关键词
声源定位/声源跟踪/神经网络/深度学习Key words
sound source localization/sound source tracking/neural networks/deep learning分类
信息技术与安全科学引用本文复制引用
陈喆,宋登鏊,王一宇,殷福亮..基于深度学习的声源定位与跟踪综述[J].数据采集与处理,2026,41(2):371-396,26.基金项目
国家自然科学基金(62271103,61871066). National Natural Science Foundation of China(Nos.62271103,61871066). （62271103,61871066）
