  Recent literature has demonstrated that the use of per-channel energy
normalization (PCEN), has significant performance improvements over traditional
log-scaled mel-frequency spectrograms in acoustic sound event detection (SED)
in a multi-class setting with overlapping events. However, the configuration of
PCEN's parameters is sensitive to the recording environment, the
characteristics of the class of events of interest, and the presence of
multiple overlapping events. This leads to improvements on a class-by-class
basis, but poor cross-class performance. In this article, we experiment using
PCEN spectrograms as an alternative method for SED in urban audio using the
UrbanSED dataset, demonstrating per-class improvements based on parameter
configuration. Furthermore, we address cross-class performance with PCEN using
a novel method, Multi-Rate PCEN (MRPCEN). We demonstrate cross-class SED
performance with MRPCEN, demonstrating improvements to cross-class performance
compared to traditional single-rate PCEN.
