  Sound event localization and detection (SELD) is an emerging research topic
that aims to unify the tasks of sound event detection and direction-of-arrival
estimation. As a result, SELD inherits the challenges of both tasks, such as
noise, reverberation, interference, polyphony, and non-stationarity of sound
sources. Furthermore, SELD often faces an additional challenge of assigning
correct correspondences between the detected sound classes and directions of
arrival to multiple overlapping sound events. Previous studies have shown that
unknown interferences in reverberant environments often cause major degradation
in the performance of SELD systems. To further understand the challenges of the
SELD task, we performed a detailed error analysis on two of our SELD systems,
which both ranked second in the team category of DCASE SELD Challenge, one in
2020 and one in 2021. Experimental results indicate polyphony as the main
challenge in SELD, due to the difficulty in detecting all sound events of
interest. In addition, the SELD systems tend to make fewer errors for the
polyphonic scenario that is dominant in the training set.
