  This paper introduces a model of environmental acoustic scenes which adopts a
morphological approach by ab-stracting temporal structures of acoustic scenes.
To demonstrate its potential, this model is employed to evaluate the
performance of a large set of acoustic events detection systems. This model
allows us to explicitly control key morphological aspects of the acoustic scene
and isolate their impact on the performance of the system under evaluation.
Thus, more information can be gained on the behavior of evaluated systems,
providing guidance for further improvements. The proposed model is validated
using submitted systems from the IEEE DCASE Challenge; results indicate that
the proposed scheme is able to successfully build datasets useful for
evaluating some aspects the performance of event detection systems, more
particularly their robustness to new listening conditions and the increasing
level of background sounds.
