This is a dataset of 600 simulated sound scenes of 45s each representing urban sound environments, simulated using the simScene Matlab library (https://bitbucket.org/mlagrange/simscene). The dataset is divided in two parts with a train subset (400 scenes) and a test subset (200 scenes) for the development of learning-based models. Each scene is composed of three main sources (traffic, human voices and birds) according to an original scenario, which is composed semi-randomly conditionally to five ambiances: park, quiet street, noisy street, very noisy street and square. Separate channels for the contribution of each source are available. The base audio files used for simulation are obtained from Freesound (https://freesound.org) and LibriSpeech (http://www.openslr.org/12). The sound scenes are scaled according to a playback sound level in dB, which is drawn randomly but remains plausible according to the ambiance.