NBM：欧洲夜间迁徙鸟类声学监测的开放数据集
NBM: an Open Dataset for the Acoustic Monitoring of Nocturnal Migratory Birds in Europe
AI总结：
本研究提出NBM数据集，含西古北界117种鸟类的13,359条带注释鸣声，并训练两阶段深度检测模型，在45个主要物种上达到与基于更大数据集的最先进系统相当的精度，推动开放科学倡议。
摘要：
迁徙鸟类种群持续面临的威胁凸显了亟需有效的监测技术以助力其保护。其中，被动声学监测是一种重要工具，尤其适用于难以通过其他方式追踪的夜间迁徙物种。本研究介绍了夜间鸟类迁徙（NBM）数据集，该数据集包含来自西古北界117个物种的13,359条带注释的鸣声记录。数据集包含精确的时间和频率注释，由法国各地的数十名鸟类爱好者收集，从而支持新颖的下游声学分析。具体而言，我们通过训练一个专为音频数据处理而设计的原创两阶段深度目标检测模型，证明了该数据库的实用性。该模型能够在声谱图中精确定位鸟类叫声，并在数据集的45个主要物种上展现出与基于更大音频集合训练的最先进系统相当的竞争性精度。这些结果凸显了推动类似开放科学倡议以获取昂贵但宝贵的音频文件细粒度注释的价值。所有数据和代码均已公开提供。
英文摘要：
The persisting threats on migratory bird populations highlight the urgent need for effective monitoring techniques that could assist in their conservation. Among these, passive acoustic monitoring is an essential tool, particularly for nocturnal migratory species that are difficult to track otherwise. This work presents the Nocturnal Bird Migration (NBM) dataset, a collection of 13,359 annotated vocalizations from 117 species of the Western Palearctic. The dataset includes precise time and frequency annotations, gathered by dozens of bird enthusiasts across France, enabling novel downstream acoustic analysis. In particular, we prove the utility of this database by training an original two-stage deep object detection model tailored for the processing of audio data. While allowing the precise localization of bird calls in spectrograms, this model shows competitive accuracy on the 45 main species of the dataset with state-of-the-art systems trained on much larger audio collections. These results highlight the interest of fostering similar open-science initiatives to acquire costly but valuable fine-grained annotations of audio files. All data and code are made openly available.
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