TUT Sound Events 2018 - Circular array, Anechoic and Synthetic Impulse Response Dataset

Tampere University of Technology (TUT) Sound Events 2018 - Circular array, Anechoic and Synthetic Impulse Response Dataset This dataset consists of simulated anechoic circular-array format recordings with stationary point sources each associated with a spatial coordinate. The dataset consists of three sub-datasets with a) maximum one temporally overlapping sound events, b) maximum two temporally overlapping sound events, and c) maximum three temporally overlapping sound events. Each of the sub-datasets has three cross-validation splits, that consists of 240 recordings of about 30 seconds long for training split and 60 recordings of the same length for the testing split. For each recording, the metadata file with the same name consists of the sound event name, the temporal onset and offset time (in seconds), spatial location in azimuth and elevation angles (in degrees), and distance from the microphone (in meters). The isolated sound events were taken from the DCASE 2016 task 2 dataset. This dataset consists of 11 sound event classes such as Clearing throat, Coughing, Door knock, Door slam, Drawer, Human laughter, Keyboard, Keys (put on a table), Page turning, Phone ringing and Speech. The sound events are randomly placed in a spatial grid with 10-degree resolution in full azimuth and [-60 60) degree elevation angles. Additionally, the sound events are placed at a random distance of [1 10] meters from the microphone. The license of the dataset can be found in the LICENSE file. The rest of the nine zip files consists of datasets for a given split and overlap. For example, the ov3_split1.zip file consists of the audio and metadata folders for the case of maximum three temporally overlapping sound events (ov3) and the first cross-validation split (split1). Within each audio/metadata folder, the filenames for training split have the 'train' prefix, while the testing split filenames have the 'test' prefix. This dataset was collected as part of the 'Sound event localization and detection of overlapping sources using convolutional recurrent neural network' work.坦佩雷理工大学（Tampere University of Technology, TUT）2018年声事件数据集——圆形阵列、无回响与合成冲激响应数据集。本数据集包含模拟生成的无回响圆形阵列格式录音，声源为固定点声源，每个声源均关联对应的空间坐标。数据集分为三个子数据集，分别对应：a) 最多1个时域重叠声事件；b) 最多2个时域重叠声事件；c) 最多3个时域重叠声事件。每个子数据集均包含3组交叉验证划分，每组划分均设有训练集与测试集：训练集包含240段时长约30秒的录音，测试集包含60段等长的录音。每段录音对应一个同名元数据文件，其中包含声事件名称、时域起始与结束时间（单位：秒）、以方位角和俯仰角表示的空间位置（单位：度），以及与麦克风的距离（单位：米）。本数据集所用的孤立声事件均取自DCASE 2016任务2数据集。本数据集涵盖11类声事件，具体包括：清嗓子、咳嗽、敲门声、猛关门声、抽屉开关声、人类笑声、键盘敲击声、钥匙放置桌面声、翻页声、电话铃声与语音。声事件被随机放置在空间网格中：方位角覆盖全范围，分辨率为10度；俯仰角范围为[-60, 60)度。此外，声事件与麦克风的距离随机取自[1, 10]米区间。数据集的授权协议可在LICENSE文件中查看。其余9个压缩包均为对应重叠场景与划分方式的数据集。例如，ov3_split1.zip包含最多3个时域重叠声事件（ov3）与第1组交叉验证划分（split1）场景下的音频与元数据文件夹。在每个音频/元数据文件夹中，训练集文件以"train"作为文件名前缀，测试集文件则以"test"作为文件名前缀。本数据集是"基于卷积循环神经网络（Convolutional Recurrent Neural Network）的声事件定位与重叠声源检测"研究工作的配套数据集。