标题： 多类声学数据集和交互式工具用于在现实环境中分析无人机特征 显示英文标题

标题： A Multiclass Acoustic Dataset and Interactive Tool for Analyzing Drone Signatures in Real-World Environments

摘要： 无人机在各个行业的快速普及带来了与隐私、安全和噪音污染相关的重大挑战。 当前的无人机检测系统主要基于视觉和雷达技术，在某些条件下存在局限性，这凸显了有效声学检测方法的必要性。 本文介绍了一个独特且全面的无人机声学特征数据集，涵盖了32种不同的类别，按品牌和型号进行区分。 该数据集包括每架无人机的原始音频记录、频谱图和梅尔频率倒谱系数（MFCC）图。 此外，我们还介绍了一个交互式网络应用程序，允许用户通过选择特定的无人机类别，聆听相关音频，并查看相应的频谱图和MFCC图。 该工具旨在促进无人机检测、分类和声学分析的研究，支持技术和教育方面的进展。 本文详细介绍了数据集的创建过程、网络应用程序的设计与实现，并提供了实验结果和用户反馈。 最后，我们讨论了潜在的应用和未来工作，以扩展和改进该项目。 显示英文摘要

摘要： The rapid proliferation of drones across various industries has introduced significant challenges related to privacy, security, and noise pollution. Current drone detection systems, primarily based on visual and radar technologies, face limitations under certain conditions, highlighting the need for effective acoustic-based detection methods. This paper presents a unique and comprehensive dataset of drone acoustic signatures, encompassing 32 different categories differentiated by brand and model. The dataset includes raw audio recordings, spectrogram plots, and Mel-frequency cepstral coefficient (MFCC) plots for each drone. Additionally, we introduce an interactive web application that allows users to explore this dataset by selecting specific drone categories, listening to the associated audio, and viewing the corresponding spectrogram and MFCC plots. This tool aims to facilitate research in drone detection, classification, and acoustic analysis, supporting both technological advancements and educational initiatives. The paper details the dataset creation process, the design and implementation of the web application, and provides experimental results and user feedback. Finally, we discuss potential applications and future work to expand and enhance the project.