Environment Classification via Blind Roomprints Estimation
Audio and Speech Processing
2023-01-27 v3 Sound
Abstract
In this paper we present a novel approach for environment classification for speech recordings, which does not require the selection of decaying reverberation tails. It is based on a multi-band RT60 analysis of blind channel estimates and achieves an accuracy of up to 93.6% on test recordings derived from the ACE corpus.
Keywords
Cite
@article{arxiv.2209.07196,
title = {Environment Classification via Blind Roomprints Estimation},
author = {Malte Baum and Luca Cuccovillo and Artem Yaroshchuk and Patrick Aichroth},
journal= {arXiv preprint arXiv:2209.07196},
year = {2023}
}