家的声音：一个面向声音事件检测的去除语音的住宅音频数据集
The Sounds of Home: A Speech-Removed Residential Audio Dataset for Sound Event Detection
AI总结：
本文构建了一个面向老年人智能家居的住宅音频数据集，通过级联预训练音频神经网络自动去除语音片段以保护隐私，同时保留其他声音事件，为家庭场景声音事件检测模型的开发与评测提供基础。
摘要：
本文提出了一个住宅音频数据集，以支持面向智能家居应用的声音事件检测研究，旨在促进老年人的身心健康。该数据集通过在8名年龄为55-80岁的参与者家中部署音频录制系统、持续7天采集构建而成。通过详细的平面图和建筑材料信息记录声学特性，以便为AI模型部署复现录制环境。开发了一种新颖的自动化语音去除流程，使用预训练的音频神经网络检测并移除包含口语语音的片段，同时保留包含其他声音事件的片段。所得数据集由符合隐私要求的音频录制组成，能够准确捕捉住宅空间内的声景和日常生活活动。本文详细介绍了数据集构建方法、利用级联模型架构的语音去除流程，以及对发声标签分布的分析，以验证语音去除过程。该数据集支持专门针对家庭应用的声音事件检测模型的开发和基准测试。
英文摘要：
This paper presents a residential audio dataset to support sound event detection research for smart home applications aimed at promoting wellbeing for older adults. The dataset is constructed by deploying audio recording systems in the homes of 8 participants aged 55-80 years for a 7-day period. Acoustic characteristics are documented through detailed floor plans and construction material information to enable replication of the recording environments for AI model deployment. A novel automated speech removal pipeline is developed, using pre-trained audio neural networks to detect and remove segments containing spoken voice, while preserving segments containing other sound events. The resulting dataset consists of privacy-compliant audio recordings that accurately capture the soundscapes and activities of daily living within residential spaces. The paper details the dataset creation methodology, the speech removal pipeline utilizing cascaded model architectures, and an analysis of the vocal label distribution to validate the speech removal process. This dataset enables the development and benchmarking of sound event detection models tailored specifically for in-home applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
