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Multi-Temporal Resolution Convolutional Neural Networks for Acoustic Scene Classification
[article]
2018
arXiv
pre-print
In this paper we present a Deep Neural Network architecture for the task of acoustic scene classification which harnesses information from increasing temporal resolutions of Mel-Spectrogram segments. This architecture is composed of separated parallel Convolutional Neural Networks which learn spectral and temporal representations for each input resolution. The resolutions are chosen to cover fine-grained characteristics of a scene's spectral texture as well as its distribution of acoustic
arXiv:1811.04419v1
fatcat:dyaxepbdavduna6bdnf2rxoywa