Dataset: InsectSound1000

InsectSound1000 is a dataset comprising more than 169000 labelled sound samples of 12 insects. The insect's sound level spans from very loud Bombus terrestris, to inaudible to human ears Aphidoletes aphidimyza. The samples were extracted from more than 1000 h of recordings made in an anechoic box with a four-channel low-noise measurement microphone array. Each sample is a four-channel wave-file of 2500 ms length, at 16 kHz sample rate and 32 bit resolution. Acoustic insect recognition holds great potential to form the basis of a digital insect sensor. Such sensors are desperately needed to automate pest monitoring and ecological monitoring. With its significant size and high-quality recordings, InsectSound1000 can be used to train data-hungry deep learning models. Used to pre-train models, it can also be leveraged to enable the development of acoustic insect recognition systems on different hardware or for different insects. Further, the methodology employed to create the dataset is presented in detail to allow for the extension of the published dataset.InsectSound1000是一款涵盖12个昆虫类别的数据集，共包含超过169000条标注音频样本。该数据集覆盖的昆虫音频声级跨度极大，从音量极高的熊蜂（Bombus terrestris），到人耳无法感知的食蚜瘿蚊（Aphidoletes aphidimyza）。所有样本均提取自消声箱内通过四通道低噪声测量麦克风阵列录制的超1000小时音频素材。每条样本均为时长2500ms、采样率16kHz、32位位深度的四通道WAVE音频文件。 声学昆虫识别技术具备成为数字化昆虫传感器核心的巨大应用潜力，而此类传感器对于实现害虫监测与生态监测的自动化至关重要。依托其庞大的数据集规模与高质量的录音素材，InsectSound1000可用于训练数据依赖型深度学习模型。若将其用于模型预训练，还可助力开发适配不同硬件平台或针对不同昆虫类别的声学昆虫识别系统。此外，本文详细阐述了该数据集的构建方法，以便后续对已发布的数据集进行扩展。