Sea bream sound recordings

This dataset contains multi-window segmented passive acoustic recordings of Gilthead Sea Bream (Sparus aurata) feeding behaviour collected in controlled recirculating aquaculture system (RAS) environments. Continuous raw audio (44.1 kHz, 16‑bit PCM) was recorded across three experimental tanks using an Aquarian Audio H2dM hydrophone. To support machine‑learning and deep‑learning research, the recordings were processed through a nine‑stage pipeline including band‑limited filtering (50–1000 Hz), RMS-based activity validation, and fixed‑length segmentation into five temporal resolutions: 1 s, 2 s, 5 s, 10 s, and 20 s. Each segment is annotated into one of four behavioural classes—Background, Pre-Feeding, Feeding, and Post-Feeding—based on synchronised behavioural logs collected during multiple feeding cycles. The repository includes the segmented audio files, metadata (tank conditions, hydrophone placement, timestamps, and behavioural labels), and documentation describing the preprocessing workflow. This dataset is intended to support reproducible research in bioacoustics, underwater signal processing, behavioural inference, and precision aquaculture.

本数据集包含多窗口分段式被动声学录音，记录对象为金头鲷（Gilthead Sea Bream, Sparus aurata）的摄食行为，采集于可控循环水养殖系统（Recirculating Aquaculture System, RAS）环境中。研究人员采用Aquarian Audio H2dM水听器，在三个试验养殖槽中采集了连续原始音频（采样率44.1kHz、16位脉冲编码调制（Pulse Code Modulation, PCM））。为支撑机器学习与深度学习相关研究，对上述录音执行了九阶段预处理流程：涵盖带限滤波（50–1000Hz）、基于均方根（Root Mean Square, RMS）的活动有效性验证，以及将音频分割为固定时长片段，共覆盖五种时间分辨率：1秒、2秒、5秒、10秒及20秒。每个片段依据多个摄食周期中同步采集的行为日志，被标注为四类行为类别之一：背景（Background）、摄食前期（Pre-Feeding）、摄食期（Feeding）及摄食后期（Post-Feeding）。该数据集仓库包含分段音频文件、元数据（含养殖槽环境参数、水听器部署位置、时间戳及行为标签），以及描述预处理工作流程的文档。本数据集旨在为生物声学、水下信号处理、行为推断及精准水产养殖领域的可复现研究提供支撑。